Overview

Dataset statistics

Number of variables62
Number of observations81
Missing cells2028
Missing cells (%)40.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.4 KiB
Average record size in memory497.6 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

airdate has constant value "2020-12-02" Constant
_embedded.show.dvdCountry.name has constant value "Ukraine" Constant
_embedded.show.dvdCountry.code has constant value "UA" Constant
_embedded.show.dvdCountry.timezone has constant value "Europe/Zaporozhye" Constant
url has a high cardinality: 81 distinct values High cardinality
name has a high cardinality: 71 distinct values High cardinality
_links.self.href has a high cardinality: 81 distinct values High cardinality
_embedded.show.url has a high cardinality: 67 distinct values High cardinality
_embedded.show.name has a high cardinality: 66 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 61 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 59 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 60 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 60 distinct values High cardinality
_embedded.show.summary has a high cardinality: 53 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 67 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 67 distinct values High cardinality
id is highly correlated with rating.average and 3 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
number is highly correlated with rating.average and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 5 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 6 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 3 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 4 other fieldsHigh correlation
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 2 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 4 other fieldsHigh correlation
id is highly correlated with url and 23 other fieldsHigh correlation
url is highly correlated with id and 46 other fieldsHigh correlation
name is highly correlated with id and 38 other fieldsHigh correlation
season is highly correlated with url and 29 other fieldsHigh correlation
number is highly correlated with url and 33 other fieldsHigh correlation
type is highly correlated with url and 15 other fieldsHigh correlation
airtime is highly correlated with url and 37 other fieldsHigh correlation
airstamp is highly correlated with url and 40 other fieldsHigh correlation
runtime is highly correlated with url and 39 other fieldsHigh correlation
summary is highly correlated with id and 37 other fieldsHigh correlation
rating.average is highly correlated with url and 5 other fieldsHigh correlation
image.medium is highly correlated with id and 36 other fieldsHigh correlation
image.original is highly correlated with id and 36 other fieldsHigh correlation
_links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.language is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 28 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 21 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 30 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with url and 32 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with url and 42 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 38 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.updated is highly correlated with url and 28 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with url and 37 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 36 other fieldsHigh correlation
number has 1 (1.2%) missing values Missing
runtime has 6 (7.4%) missing values Missing
summary has 68 (84.0%) missing values Missing
rating.average has 77 (95.1%) missing values Missing
image.medium has 67 (82.7%) missing values Missing
image.original has 67 (82.7%) missing values Missing
_embedded.show.language has 1 (1.2%) missing values Missing
_embedded.show.runtime has 20 (24.7%) missing values Missing
_embedded.show.averageRuntime has 4 (4.9%) missing values Missing
_embedded.show.ended has 46 (56.8%) missing values Missing
_embedded.show.officialSite has 13 (16.0%) missing values Missing
_embedded.show.rating.average has 75 (92.6%) missing values Missing
_embedded.show.network has 81 (100.0%) missing values Missing
_embedded.show.webChannel.id has 2 (2.5%) missing values Missing
_embedded.show.webChannel.name has 2 (2.5%) missing values Missing
_embedded.show.webChannel.country has 81 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 32 (39.5%) missing values Missing
_embedded.show.dvdCountry has 81 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 79 (97.5%) missing values Missing
_embedded.show.externals.thetvdb has 28 (34.6%) missing values Missing
_embedded.show.externals.imdb has 49 (60.5%) missing values Missing
_embedded.show.image.medium has 7 (8.6%) missing values Missing
_embedded.show.image.original has 7 (8.6%) missing values Missing
_embedded.show.summary has 16 (19.8%) missing values Missing
image has 81 (100.0%) missing values Missing
_embedded.show.webChannel.country.name has 38 (46.9%) missing values Missing
_embedded.show.webChannel.country.code has 38 (46.9%) missing values Missing
_embedded.show.webChannel.country.timezone has 38 (46.9%) missing values Missing
_embedded.show._links.nextepisode.href has 75 (92.6%) missing values Missing
_embedded.show.network.id has 73 (90.1%) missing values Missing
_embedded.show.network.name has 73 (90.1%) missing values Missing
_embedded.show.network.country.name has 73 (90.1%) missing values Missing
_embedded.show.network.country.code has 73 (90.1%) missing values Missing
_embedded.show.network.country.timezone has 73 (90.1%) missing values Missing
_embedded.show.network.officialSite has 81 (100.0%) missing values Missing
_embedded.show.webChannel has 81 (100.0%) missing values Missing
_embedded.show.image has 81 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 80 (98.8%) missing values Missing
_embedded.show.dvdCountry.code has 80 (98.8%) missing values Missing
_embedded.show.dvdCountry.timezone has 80 (98.8%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.url is uniformly distributed Uniform
_embedded.show.name is uniformly distributed Uniform
_embedded.show.premiered is uniformly distributed Uniform
_embedded.show.officialSite is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show.image.medium is uniformly distributed Uniform
_embedded.show.image.original is uniformly distributed Uniform
_embedded.show.summary is uniformly distributed Uniform
_embedded.show._links.self.href is uniformly distributed Uniform
_embedded.show._links.previousepisode.href is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show.network.country.name is uniformly distributed Uniform
_embedded.show.network.country.code is uniformly distributed Uniform
_embedded.show.network.country.timezone is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:35:56.662599
Analysis finished2022-09-06 02:36:12.785392
Duration16.12 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2026054.543
Minimum1945144
Maximum2386103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:12.857564image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1945144
5-th percentile1965919
Q11976155
median1979362
Q32030018
95-th percentile2205966
Maximum2386103
Range440959
Interquartile range (IQR)53863

Descriptive statistics

Standard deviation90342.7363
Coefficient of variation (CV)0.04459047591
Kurtosis3.432024423
Mean2026054.543
Median Absolute Deviation (MAD)7795
Skewness1.955122666
Sum164110418
Variance8161810002
MonotonicityNot monotonic
2022-09-05T21:36:12.971288image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19727821
 
1.2%
20011041
 
1.2%
19776331
 
1.2%
19776321
 
1.2%
19761861
 
1.2%
19761851
 
1.2%
19761551
 
1.2%
19761541
 
1.2%
19761371
 
1.2%
19761361
 
1.2%
Other values (71)71
87.7%
ValueCountFrequency (%)
19451441
1.2%
19588651
1.2%
19600291
1.2%
19644931
1.2%
19659191
1.2%
19685481
1.2%
19685491
1.2%
19701841
1.2%
19715671
1.2%
19727821
1.2%
ValueCountFrequency (%)
23861031
1.2%
23180961
1.2%
22396071
1.2%
22059671
1.2%
22059661
1.2%
21926221
1.2%
21820801
1.2%
21761191
1.2%
21748981
1.2%
21661931
1.2%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size776.0 B
https://www.tvmaze.com/episodes/1972782/kontakty-1x28-kontakty-v-telefone-sergea-lazareva-timati-polina-gagarina-vlad-topalov-ida-galic
 
1
https://www.tvmaze.com/episodes/2001104/red-table-talk-the-estefans-1x08-powerful-life-lessons-from-supreme-court-justice-sonia-sotomayor
 
1
https://www.tvmaze.com/episodes/1977633/to-love-1x22-episode-22
 
1
https://www.tvmaze.com/episodes/1977632/to-love-1x21-episode-21
 
1
https://www.tvmaze.com/episodes/1976186/psych-hunter-1x20-episode-20
 
1
Other values (76)
76 

Length

Max length140
Median length105
Mean length82.20987654
Min length58

Characters and Unicode

Total characters6659
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1972782/kontakty-1x28-kontakty-v-telefone-sergea-lazareva-timati-polina-gagarina-vlad-topalov-ida-galic
2nd rowhttps://www.tvmaze.com/episodes/1979223/kotiki-1x03-seria-3
3rd rowhttps://www.tvmaze.com/episodes/1971567/mermaid-prince-2x07-episode-7
4th rowhttps://www.tvmaze.com/episodes/1983072/wan-sheng-jie-2x10-all-products-funds-were-spent-on-this-episode
5th rowhttps://www.tvmaze.com/episodes/2386103/xian-feng-jian-yu-lu-1x44-episode-44

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1972782/kontakty-1x28-kontakty-v-telefone-sergea-lazareva-timati-polina-gagarina-vlad-topalov-ida-galic1
 
1.2%
https://www.tvmaze.com/episodes/2001104/red-table-talk-the-estefans-1x08-powerful-life-lessons-from-supreme-court-justice-sonia-sotomayor1
 
1.2%
https://www.tvmaze.com/episodes/1977633/to-love-1x22-episode-221
 
1.2%
https://www.tvmaze.com/episodes/1977632/to-love-1x21-episode-211
 
1.2%
https://www.tvmaze.com/episodes/1976186/psych-hunter-1x20-episode-201
 
1.2%
https://www.tvmaze.com/episodes/1976185/psych-hunter-1x19-episode-191
 
1.2%
https://www.tvmaze.com/episodes/1976155/new-face-1x14-episode-141
 
1.2%
https://www.tvmaze.com/episodes/1976154/new-face-1x13-episode-131
 
1.2%
https://www.tvmaze.com/episodes/1976137/insect-detective-1x24-episode-241
 
1.2%
https://www.tvmaze.com/episodes/1976136/insect-detective-1x23-episode-231
 
1.2%
Other values (71)71
87.7%

Length

2022-09-05T21:36:13.086932image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1972782/kontakty-1x28-kontakty-v-telefone-sergea-lazareva-timati-polina-gagarina-vlad-topalov-ida-galic1
 
1.2%
https://www.tvmaze.com/episodes/1979223/kotiki-1x03-seria-31
 
1.2%
https://www.tvmaze.com/episodes/1971567/mermaid-prince-2x07-episode-71
 
1.2%
https://www.tvmaze.com/episodes/1983072/wan-sheng-jie-2x10-all-products-funds-were-spent-on-this-episode1
 
1.2%
https://www.tvmaze.com/episodes/2386103/xian-feng-jian-yu-lu-1x44-episode-441
 
1.2%
https://www.tvmaze.com/episodes/1985615/yi-nian-yong-heng-1x19-episode-191
 
1.2%
https://www.tvmaze.com/episodes/2030018/dolls-frontline-2x10-episode-101
 
1.2%
https://www.tvmaze.com/episodes/1973540/please-wait-brother-1x19-episode-191
 
1.2%
https://www.tvmaze.com/episodes/1973541/please-wait-brother-1x20-episode-201
 
1.2%
https://www.tvmaze.com/episodes/2066367/chu-feng-yi-dian-shizi-1x04-episode-41
 
1.2%
Other values (71)71
87.7%

Most occurring characters

ValueCountFrequency (%)
e571
 
8.6%
-513
 
7.7%
s429
 
6.4%
t411
 
6.2%
/405
 
6.1%
o367
 
5.5%
w281
 
4.2%
a277
 
4.2%
i267
 
4.0%
p255
 
3.8%
Other values (30)2883
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4562
68.5%
Decimal Number936
 
14.1%
Other Punctuation648
 
9.7%
Dash Punctuation513
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e571
12.5%
s429
 
9.4%
t411
 
9.0%
o367
 
8.0%
w281
 
6.2%
a277
 
6.1%
i267
 
5.9%
p255
 
5.6%
m231
 
5.1%
d195
 
4.3%
Other values (16)1278
28.0%
Decimal Number
ValueCountFrequency (%)
1226
24.1%
2125
13.4%
0116
12.4%
9106
11.3%
785
 
9.1%
460
 
6.4%
858
 
6.2%
656
 
6.0%
353
 
5.7%
551
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/405
62.5%
.162
 
25.0%
:81
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-513
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4562
68.5%
Common2097
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e571
12.5%
s429
 
9.4%
t411
 
9.0%
o367
 
8.0%
w281
 
6.2%
a277
 
6.1%
i267
 
5.9%
p255
 
5.6%
m231
 
5.1%
d195
 
4.3%
Other values (16)1278
28.0%
Common
ValueCountFrequency (%)
-513
24.5%
/405
19.3%
1226
10.8%
.162
 
7.7%
2125
 
6.0%
0116
 
5.5%
9106
 
5.1%
785
 
4.1%
:81
 
3.9%
460
 
2.9%
Other values (4)218
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII6659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e571
 
8.6%
-513
 
7.7%
s429
 
6.4%
t411
 
6.2%
/405
 
6.1%
o367
 
5.5%
w281
 
4.2%
a277
 
4.2%
i267
 
4.0%
p255
 
3.8%
Other values (30)2883
43.3%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct71
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size776.0 B
Episode 19
 
4
Episode 10
 
3
Episode 2
 
2
Episode 7
 
2
Episode 20
 
2
Other values (66)
68 

Length

Max length86
Median length69
Mean length20.20987654
Min length4

Characters and Unicode

Total characters1637
Distinct characters128
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)79.0%

Sample

1st rowКОНТАКТЫ в телефоне Сергея Лазарева: Тимати, Полина Гагарина, Влад Топалов, Ида Галич
2nd rowСерия 3
3rd rowEpisode 7
4th rowAll products funds were spent on this episode
5th rowEpisode 44

Common Values

ValueCountFrequency (%)
Episode 194
 
4.9%
Episode 103
 
3.7%
Episode 22
 
2.5%
Episode 72
 
2.5%
Episode 202
 
2.5%
Episode 92
 
2.5%
Episode 142
 
2.5%
Episode 241
 
1.2%
Alkene Redox Reactions1
 
1.2%
Episode 11
 
1.2%
Other values (61)61
75.3%

Length

2022-09-05T21:36:13.193385image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode35
 
12.8%
5
 
1.8%
194
 
1.5%
93
 
1.1%
a3
 
1.1%
143
 
1.1%
the3
 
1.1%
103
 
1.1%
23
 
1.1%
73
 
1.1%
Other values (199)208
76.2%

Most occurring characters

ValueCountFrequency (%)
192
 
11.7%
e127
 
7.8%
o90
 
5.5%
i78
 
4.8%
s68
 
4.2%
a63
 
3.8%
d59
 
3.6%
t56
 
3.4%
r55
 
3.4%
p52
 
3.2%
Other values (118)797
48.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1074
65.6%
Uppercase Letter251
 
15.3%
Space Separator192
 
11.7%
Decimal Number85
 
5.2%
Other Punctuation28
 
1.7%
Math Symbol2
 
0.1%
Close Punctuation2
 
0.1%
Open Punctuation2
 
0.1%
Dash Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e127
 
11.8%
o90
 
8.4%
i78
 
7.3%
s68
 
6.3%
a63
 
5.9%
d59
 
5.5%
t56
 
5.2%
r55
 
5.1%
p52
 
4.8%
n42
 
3.9%
Other values (53)384
35.8%
Uppercase Letter
ValueCountFrequency (%)
E41
 
16.3%
S17
 
6.8%
T12
 
4.8%
C12
 
4.8%
A12
 
4.8%
Т11
 
4.4%
B10
 
4.0%
D8
 
3.2%
О7
 
2.8%
M7
 
2.8%
Other values (33)114
45.4%
Decimal Number
ValueCountFrequency (%)
123
27.1%
216
18.8%
411
12.9%
010
11.8%
78
 
9.4%
98
 
9.4%
34
 
4.7%
52
 
2.4%
62
 
2.4%
81
 
1.2%
Other Punctuation
ValueCountFrequency (%)
,14
50.0%
:4
 
14.3%
.3
 
10.7%
&2
 
7.1%
"2
 
7.1%
!2
 
7.1%
/1
 
3.6%
Space Separator
ValueCountFrequency (%)
192
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1042
63.7%
Common312
 
19.1%
Cyrillic283
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e127
 
12.2%
o90
 
8.6%
i78
 
7.5%
s68
 
6.5%
a63
 
6.0%
d59
 
5.7%
t56
 
5.4%
r55
 
5.3%
p52
 
5.0%
n42
 
4.0%
Other values (46)352
33.8%
Cyrillic
ValueCountFrequency (%)
а29
 
10.2%
о20
 
7.1%
и17
 
6.0%
е16
 
5.7%
н14
 
4.9%
л14
 
4.9%
р13
 
4.6%
Т11
 
3.9%
к11
 
3.9%
в9
 
3.2%
Other values (40)129
45.6%
Common
ValueCountFrequency (%)
192
61.5%
123
 
7.4%
216
 
5.1%
,14
 
4.5%
411
 
3.5%
010
 
3.2%
78
 
2.6%
98
 
2.6%
:4
 
1.3%
34
 
1.3%
Other values (12)22
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1347
82.3%
Cyrillic283
 
17.3%
None7
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
192
 
14.3%
e127
 
9.4%
o90
 
6.7%
i78
 
5.8%
s68
 
5.0%
a63
 
4.7%
d59
 
4.4%
t56
 
4.2%
r55
 
4.1%
p52
 
3.9%
Other values (62)507
37.6%
Cyrillic
ValueCountFrequency (%)
а29
 
10.2%
о20
 
7.1%
и17
 
6.0%
е16
 
5.7%
н14
 
4.9%
л14
 
4.9%
р13
 
4.6%
Т11
 
3.9%
к11
 
3.9%
в9
 
3.2%
Other values (40)129
45.6%
None
ValueCountFrequency (%)
ø2
28.6%
ó1
14.3%
í1
14.3%
á1
14.3%
æ1
14.3%
å1
14.3%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean152.2222222
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:13.275928image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)2

Descriptive statistics

Standard deviation531.5968162
Coefficient of variation (CV)3.492241858
Kurtosis9.210441551
Mean152.2222222
Median Absolute Deviation (MAD)0
Skewness3.313995705
Sum12330
Variance282595.175
MonotonicityNot monotonic
2022-09-05T21:36:13.363793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
149
60.5%
29
 
11.1%
20206
 
7.4%
44
 
4.9%
33
 
3.7%
73
 
3.7%
101
 
1.2%
111
 
1.2%
51
 
1.2%
181
 
1.2%
Other values (3)3
 
3.7%
ValueCountFrequency (%)
149
60.5%
29
 
11.1%
33
 
3.7%
44
 
4.9%
51
 
1.2%
73
 
3.7%
81
 
1.2%
101
 
1.2%
111
 
1.2%
141
 
1.2%
ValueCountFrequency (%)
20206
7.4%
311
 
1.2%
181
 
1.2%
141
 
1.2%
111
 
1.2%
101
 
1.2%
81
 
1.2%
73
3.7%
51
 
1.2%
44
4.9%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)53.8%
Missing1
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean30.3375
Minimum1
Maximum329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:13.460572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q17
median15
Q330.75
95-th percentile94.6
Maximum329
Range328
Interquartile range (IQR)23.75

Descriptive statistics

Standard deviation51.85323586
Coefficient of variation (CV)1.709212554
Kurtosis20.69172043
Mean30.3375
Median Absolute Deviation (MAD)9
Skewness4.248861013
Sum2427
Variance2688.75807
MonotonicityNot monotonic
2022-09-05T21:36:13.563202image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
195
 
6.2%
174
 
4.9%
114
 
4.9%
104
 
4.9%
44
 
4.9%
94
 
4.9%
24
 
4.9%
14
 
4.9%
73
 
3.7%
33
 
3.7%
Other values (33)41
50.6%
ValueCountFrequency (%)
14
4.9%
24
4.9%
33
3.7%
44
4.9%
51
 
1.2%
62
2.5%
73
3.7%
82
2.5%
94
4.9%
104
4.9%
ValueCountFrequency (%)
3291
1.2%
2881
1.2%
1431
1.2%
1061
1.2%
941
1.2%
821
1.2%
771
1.2%
601
1.2%
571
1.2%
552
2.5%

type
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size776.0 B
regular
80 
significant_special
 
1

Length

Max length19
Median length7
Mean length7.148148148
Min length7

Characters and Unicode

Total characters579
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.2%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular80
98.8%
significant_special1
 
1.2%

Length

2022-09-05T21:36:13.654278image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:13.739247image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular80
98.8%
significant_special1
 
1.2%

Most occurring characters

ValueCountFrequency (%)
r160
27.6%
a82
14.2%
e81
14.0%
g81
14.0%
l81
14.0%
u80
13.8%
i4
 
0.7%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter578
99.8%
Connector Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r160
27.7%
a82
14.2%
e81
14.0%
g81
14.0%
l81
14.0%
u80
13.8%
i4
 
0.7%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin578
99.8%
Common1
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r160
27.7%
a82
14.2%
e81
14.0%
g81
14.0%
l81
14.0%
u80
13.8%
i4
 
0.7%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Common
ValueCountFrequency (%)
_1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r160
27.6%
a82
14.2%
e81
14.0%
g81
14.0%
l81
14.0%
u80
13.8%
i4
 
0.7%
s2
 
0.3%
n2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.7%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size776.0 B
2020-12-02
81 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters810
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-02
2nd row2020-12-02
3rd row2020-12-02
4th row2020-12-02
5th row2020-12-02

Common Values

ValueCountFrequency (%)
2020-12-0281
100.0%

Length

2022-09-05T21:36:13.813070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:13.897317image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0281
100.0%

Most occurring characters

ValueCountFrequency (%)
2324
40.0%
0243
30.0%
-162
20.0%
181
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number648
80.0%
Dash Punctuation162
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2324
50.0%
0243
37.5%
181
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2324
40.0%
0243
30.0%
-162
20.0%
181
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2324
40.0%
0243
30.0%
-162
20.0%
181
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size776.0 B
42 
20:00
17 
12:00
 
4
10:00
 
4
06:00
 
2
Other values (10)
12 

Length

Max length5
Median length0
Mean length2.407407407
Min length0

Characters and Unicode

Total characters195
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.9%

Sample

1st row12:00
2nd row
3rd row11:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
42
51.9%
20:0017
21.0%
12:004
 
4.9%
10:004
 
4.9%
06:002
 
2.5%
21:002
 
2.5%
00:002
 
2.5%
11:001
 
1.2%
05:001
 
1.2%
17:351
 
1.2%
Other values (5)5
 
6.2%

Length

2022-09-05T21:36:13.971527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0017
43.6%
12:004
 
10.3%
10:004
 
10.3%
06:002
 
5.1%
21:002
 
5.1%
00:002
 
5.1%
11:001
 
2.6%
05:001
 
2.6%
17:351
 
2.6%
18:001
 
2.6%
Other values (4)4
 
10.3%

Most occurring characters

ValueCountFrequency (%)
0101
51.8%
:39
 
20.0%
225
 
12.8%
118
 
9.2%
54
 
2.1%
62
 
1.0%
32
 
1.0%
82
 
1.0%
71
 
0.5%
91
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number156
80.0%
Other Punctuation39
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0101
64.7%
225
 
16.0%
118
 
11.5%
54
 
2.6%
62
 
1.3%
32
 
1.3%
82
 
1.3%
71
 
0.6%
91
 
0.6%
Other Punctuation
ValueCountFrequency (%)
:39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common195
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0101
51.8%
:39
 
20.0%
225
 
12.8%
118
 
9.2%
54
 
2.1%
62
 
1.0%
32
 
1.0%
82
 
1.0%
71
 
0.5%
91
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0101
51.8%
:39
 
20.0%
225
 
12.8%
118
 
9.2%
54
 
2.1%
62
 
1.0%
32
 
1.0%
82
 
1.0%
71
 
0.5%
91
 
0.5%

airstamp
Categorical

HIGH CORRELATION

Distinct21
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size776.0 B
2020-12-02T12:00:00+00:00
44 
2020-12-02T04:00:00+00:00
2020-12-02T11:00:00+00:00
 
4
2020-12-02T02:00:00+00:00
 
4
2020-12-02T17:00:00+00:00
 
3
Other values (16)
19 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2025
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)16.0%

Sample

1st row2020-12-02T00:00:00+00:00
2nd row2020-12-02T00:00:00+00:00
3rd row2020-12-02T02:00:00+00:00
4th row2020-12-02T02:00:00+00:00
5th row2020-12-02T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-02T12:00:00+00:0044
54.3%
2020-12-02T04:00:00+00:007
 
8.6%
2020-12-02T11:00:00+00:004
 
4.9%
2020-12-02T02:00:00+00:004
 
4.9%
2020-12-02T17:00:00+00:003
 
3.7%
2020-12-02T15:00:00+00:002
 
2.5%
2020-12-02T13:00:00+00:002
 
2.5%
2020-12-02T00:00:00+00:002
 
2.5%
2020-12-02T09:30:00+00:001
 
1.2%
2020-12-02T10:00:00+00:001
 
1.2%
Other values (11)11
 
13.6%

Length

2022-09-05T21:36:14.079029image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-02t12:00:00+00:0044
54.3%
2020-12-02t04:00:00+00:007
 
8.6%
2020-12-02t11:00:00+00:004
 
4.9%
2020-12-02t02:00:00+00:004
 
4.9%
2020-12-02t17:00:00+00:003
 
3.7%
2020-12-02t15:00:00+00:002
 
2.5%
2020-12-02t13:00:00+00:002
 
2.5%
2020-12-02t00:00:00+00:002
 
2.5%
2020-12-02t05:35:00+00:001
 
1.2%
2020-12-03t02:25:00+00:001
 
1.2%
Other values (11)11
 
13.6%

Most occurring characters

ValueCountFrequency (%)
0912
45.0%
2372
18.4%
:243
 
12.0%
-162
 
8.0%
1144
 
7.1%
T81
 
4.0%
+81
 
4.0%
48
 
0.4%
57
 
0.3%
37
 
0.3%
Other values (3)8
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1458
72.0%
Other Punctuation243
 
12.0%
Dash Punctuation162
 
8.0%
Uppercase Letter81
 
4.0%
Math Symbol81
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0912
62.6%
2372
25.5%
1144
 
9.9%
48
 
0.5%
57
 
0.5%
37
 
0.5%
74
 
0.3%
93
 
0.2%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:243
100.0%
Dash Punctuation
ValueCountFrequency (%)
-162
100.0%
Uppercase Letter
ValueCountFrequency (%)
T81
100.0%
Math Symbol
ValueCountFrequency (%)
+81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1944
96.0%
Latin81
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0912
46.9%
2372
19.1%
:243
 
12.5%
-162
 
8.3%
1144
 
7.4%
+81
 
4.2%
48
 
0.4%
57
 
0.4%
37
 
0.4%
74
 
0.2%
Other values (2)4
 
0.2%
Latin
ValueCountFrequency (%)
T81
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2025
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0912
45.0%
2372
18.4%
:243
 
12.0%
-162
 
8.0%
1144
 
7.1%
T81
 
4.0%
+81
 
4.0%
48
 
0.4%
57
 
0.3%
37
 
0.3%
Other values (3)8
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)45.3%
Missing6
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean39.54666667
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:14.177391image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q117
median37
Q345
95-th percentile120
Maximum300
Range298
Interquartile range (IQR)28

Descriptive statistics

Standard deviation40.74916459
Coefficient of variation (CV)1.030407061
Kurtosis22.49045825
Mean39.54666667
Median Absolute Deviation (MAD)12
Skewness3.989508514
Sum2966
Variance1660.494414
MonotonicityNot monotonic
2022-09-05T21:36:14.273445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4520
24.7%
57
 
8.6%
304
 
4.9%
253
 
3.7%
193
 
3.7%
402
 
2.5%
352
 
2.5%
132
 
2.5%
412
 
2.5%
602
 
2.5%
Other values (24)28
34.6%
(Missing)6
 
7.4%
ValueCountFrequency (%)
21
 
1.2%
41
 
1.2%
57
8.6%
71
 
1.2%
81
 
1.2%
91
 
1.2%
111
 
1.2%
121
 
1.2%
132
 
2.5%
141
 
1.2%
ValueCountFrequency (%)
3001
 
1.2%
1281
 
1.2%
1211
 
1.2%
1202
 
2.5%
901
 
1.2%
691
 
1.2%
602
 
2.5%
481
 
1.2%
471
 
1.2%
4520
24.7%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct12
Distinct (%)92.3%
Missing68
Missing (%)84.0%
Memory size776.0 B
<p>Twin stars create an oxygen-rich atmosphere on Eden, where a teeming biosphere may parallel seasonal cycles of predation and reproduction on Earth.</p>
<p>Katya's ready for love, and she wants to do it now. Trixie explains to her what love is, and Katya designs her perfect man.</p>
<p>This issue could be a continuation of the series Better Houses about Castles of Ukraine. But Zhenya Sinelnikov decided to show us a slightly different route. Following from Kiev to Lviv, we will stop at a picturesque canyon, show a place with houses, right for a photo on Instagram, visit the famous tunnel of love. First of all, we will show the Ukrainian Disneyland - Victoria film studio, there is even a real Iron Throne! Next, we are waiting for the autumn Radomyshl, a visit to a shelter for bears, and at the end of the three castles of Ukraine - Pidhretsky Castle, Zolochy Castle, Olesky Castle.</p>
<p>Настало время расплаты и жестких вопросов для Владимира Маркони от ковбоев, амазонок и Сергея Мезенцева. Смотрим!</p>
<p>During their occupation of large parts of Europe, the Nazis systematically looted foreign countries for art, gold and other items holding financial or cultural value. Often for any larger purpose, but for their own, egocentric, criminal gain.</p>
Other values (7)

Length

Max length610
Median length182
Mean length223.1538462
Min length120

Characters and Unicode

Total characters2901
Distinct characters96
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)84.6%

Sample

1st row<p>Katya's ready for love, and she wants to do it now. Trixie explains to her what love is, and Katya designs her perfect man.</p>
2nd row<p>This issue could be a continuation of the series Better Houses about Castles of Ukraine. But Zhenya Sinelnikov decided to show us a slightly different route. Following from Kiev to Lviv, we will stop at a picturesque canyon, show a place with houses, right for a photo on Instagram, visit the famous tunnel of love. First of all, we will show the Ukrainian Disneyland - Victoria film studio, there is even a real Iron Throne! Next, we are waiting for the autumn Radomyshl, a visit to a shelter for bears, and at the end of the three castles of Ukraine - Pidhretsky Castle, Zolochy Castle, Olesky Castle.</p>
3rd row<p>Настало время расплаты и жестких вопросов для Владимира Маркони от ковбоев, амазонок и Сергея Мезенцева. Смотрим!</p>
4th row<p>During their occupation of large parts of Europe, the Nazis systematically looted foreign countries for art, gold and other items holding financial or cultural value. Often for any larger purpose, but for their own, egocentric, criminal gain.</p>
5th row<p>Science and technology is marching on as the world enters the 1920's. But Americans have more to reckon with than just a new decade: every state in the country has gone "dry".</p>

Common Values

ValueCountFrequency (%)
<p>Twin stars create an oxygen-rich atmosphere on Eden, where a teeming biosphere may parallel seasonal cycles of predation and reproduction on Earth.</p>2
 
2.5%
<p>Katya's ready for love, and she wants to do it now. Trixie explains to her what love is, and Katya designs her perfect man.</p>1
 
1.2%
<p>This issue could be a continuation of the series Better Houses about Castles of Ukraine. But Zhenya Sinelnikov decided to show us a slightly different route. Following from Kiev to Lviv, we will stop at a picturesque canyon, show a place with houses, right for a photo on Instagram, visit the famous tunnel of love. First of all, we will show the Ukrainian Disneyland - Victoria film studio, there is even a real Iron Throne! Next, we are waiting for the autumn Radomyshl, a visit to a shelter for bears, and at the end of the three castles of Ukraine - Pidhretsky Castle, Zolochy Castle, Olesky Castle.</p>1
 
1.2%
<p>Настало время расплаты и жестких вопросов для Владимира Маркони от ковбоев, амазонок и Сергея Мезенцева. Смотрим!</p>1
 
1.2%
<p>During their occupation of large parts of Europe, the Nazis systematically looted foreign countries for art, gold and other items holding financial or cultural value. Often for any larger purpose, but for their own, egocentric, criminal gain.</p>1
 
1.2%
<p>Science and technology is marching on as the world enters the 1920's. But Americans have more to reckon with than just a new decade: every state in the country has gone "dry".</p>1
 
1.2%
<p>On exoplanet Atlas, dense gravity creates a thick atmosphere allowing airborne life forms to thrive — but also providing a lesson in adaptability.</p>1
 
1.2%
<p>Ants, scorpions and fireflies provide clues for biologists to conjecture about life on exoplanet Janus, including highly adaptable pentapods.</p>1
 
1.2%
<p>Welcome to the SEASON 2 of our spooky and now FESTIVE show- Too Many Spirits! Join us as we read your submitted holiday ghost stories and enjoy cocktails prepared by freshman bartender, Steven Lim.</p>1
 
1.2%
<p>Ronan Farrow enters the Hot Take octagon to discuss the rigged election, Trump's masterful Covid response, and the Me Too movement. </p>1
 
1.2%
Other values (2)2
 
2.5%
(Missing)68
84.0%

Length

2022-09-05T21:36:14.371396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the21
 
4.5%
and15
 
3.2%
to15
 
3.2%
a14
 
3.0%
of13
 
2.8%
for9
 
1.9%
on7
 
1.5%
but5
 
1.1%
in4
 
0.9%
show4
 
0.9%
Other values (300)361
77.1%

Most occurring characters

ValueCountFrequency (%)
454
15.6%
e242
 
8.3%
o189
 
6.5%
t178
 
6.1%
a177
 
6.1%
n167
 
5.8%
i146
 
5.0%
s142
 
4.9%
r135
 
4.7%
l89
 
3.1%
Other values (86)982
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2185
75.3%
Space Separator455
 
15.7%
Uppercase Letter111
 
3.8%
Other Punctuation81
 
2.8%
Math Symbol52
 
1.8%
Dash Punctuation6
 
0.2%
Decimal Number5
 
0.2%
Open Punctuation3
 
0.1%
Close Punctuation3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e242
 
11.1%
o189
 
8.6%
t178
 
8.1%
a177
 
8.1%
n167
 
7.6%
i146
 
6.7%
s142
 
6.5%
r135
 
6.2%
l89
 
4.1%
h88
 
4.0%
Other values (38)632
28.9%
Uppercase Letter
ValueCountFrequency (%)
R11
 
9.9%
T11
 
9.9%
F10
 
9.0%
S8
 
7.2%
E8
 
7.2%
C7
 
6.3%
B5
 
4.5%
H5
 
4.5%
A5
 
4.5%
O4
 
3.6%
Other values (16)37
33.3%
Other Punctuation
ValueCountFrequency (%)
,33
40.7%
.20
24.7%
/13
 
16.0%
!5
 
6.2%
'4
 
4.9%
"2
 
2.5%
;1
 
1.2%
:1
 
1.2%
&1
 
1.2%
?1
 
1.2%
Decimal Number
ValueCountFrequency (%)
22
40.0%
01
20.0%
91
20.0%
11
20.0%
Space Separator
ValueCountFrequency (%)
454
99.8%
 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
<26
50.0%
>26
50.0%
Dash Punctuation
ValueCountFrequency (%)
-5
83.3%
1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2201
75.9%
Common605
 
20.9%
Cyrillic95
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e242
 
11.0%
o189
 
8.6%
t178
 
8.1%
a177
 
8.0%
n167
 
7.6%
i146
 
6.6%
s142
 
6.5%
r135
 
6.1%
l89
 
4.0%
h88
 
4.0%
Other values (38)648
29.4%
Cyrillic
ValueCountFrequency (%)
о11
 
11.6%
а10
 
10.5%
е8
 
8.4%
р7
 
7.4%
и7
 
7.4%
в6
 
6.3%
т5
 
5.3%
м5
 
5.3%
л4
 
4.2%
с4
 
4.2%
Other values (16)28
29.5%
Common
ValueCountFrequency (%)
454
75.0%
,33
 
5.5%
<26
 
4.3%
>26
 
4.3%
.20
 
3.3%
/13
 
2.1%
!5
 
0.8%
-5
 
0.8%
'4
 
0.7%
(3
 
0.5%
Other values (12)16
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2804
96.7%
Cyrillic95
 
3.3%
Punctuation1
 
< 0.1%
None1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
454
16.2%
e242
 
8.6%
o189
 
6.7%
t178
 
6.3%
a177
 
6.3%
n167
 
6.0%
i146
 
5.2%
s142
 
5.1%
r135
 
4.8%
l89
 
3.2%
Other values (58)885
31.6%
Cyrillic
ValueCountFrequency (%)
о11
 
11.6%
а10
 
10.5%
е8
 
8.4%
р7
 
7.4%
и7
 
7.4%
в6
 
6.3%
т5
 
5.3%
м5
 
5.3%
л4
 
4.2%
с4
 
4.2%
Other values (16)28
29.5%
Punctuation
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
 1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)75.0%
Missing77
Missing (%)95.1%
Memory size776.0 B
9.0
7.3
10.0

Length

Max length4
Median length3
Mean length3.25
Min length3

Characters and Unicode

Total characters13
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row7.3
2nd row9.0
3rd row9.0
4th row10.0

Common Values

ValueCountFrequency (%)
9.02
 
2.5%
7.31
 
1.2%
10.01
 
1.2%
(Missing)77
95.1%

Length

2022-09-05T21:36:14.457787image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:14.543984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
9.02
50.0%
7.31
25.0%
10.01
25.0%

Most occurring characters

ValueCountFrequency (%)
.4
30.8%
04
30.8%
92
15.4%
71
 
7.7%
31
 
7.7%
11
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number9
69.2%
Other Punctuation4
30.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
04
44.4%
92
22.2%
71
 
11.1%
31
 
11.1%
11
 
11.1%
Other Punctuation
ValueCountFrequency (%)
.4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
.4
30.8%
04
30.8%
92
15.4%
71
 
7.7%
31
 
7.7%
11
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.4
30.8%
04
30.8%
92
15.4%
71
 
7.7%
31
 
7.7%
11
 
7.7%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct14
Distinct (%)100.0%
Missing67
Missing (%)82.7%
Memory size776.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/360/901421.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/286/715106.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/293/734764.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/286/715360.jpg
https://static.tvmaze.com/uploads/images/medium_landscape/286/715179.jpg
Other values (9)

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters1008
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901421.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/715106.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/293/734764.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/715360.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/286/715179.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901421.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715106.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734764.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715360.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715179.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/340/850668.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719897.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719898.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719899.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719900.jpg1
 
1.2%
Other values (4)4
 
4.9%
(Missing)67
82.7%

Length

2022-09-05T21:36:14.618841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901421.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715106.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734764.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715360.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/286/715179.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/340/850668.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719897.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719898.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719899.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719900.jpg1
 
7.1%
Other values (4)4
28.6%

Most occurring characters

ValueCountFrequency (%)
/98
 
9.7%
a84
 
8.3%
t70
 
6.9%
s70
 
6.9%
m70
 
6.9%
p56
 
5.6%
e56
 
5.6%
i42
 
4.2%
c42
 
4.2%
.42
 
4.2%
Other values (22)378
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter714
70.8%
Other Punctuation154
 
15.3%
Decimal Number126
 
12.5%
Connector Punctuation14
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a84
11.8%
t70
9.8%
s70
9.8%
m70
9.8%
p56
 
7.8%
e56
 
7.8%
i42
 
5.9%
c42
 
5.9%
d42
 
5.9%
l28
 
3.9%
Other values (8)154
21.6%
Decimal Number
ValueCountFrequency (%)
721
16.7%
817
13.5%
916
12.7%
214
11.1%
114
11.1%
511
8.7%
610
7.9%
09
7.1%
38
 
6.3%
46
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/98
63.6%
.42
27.3%
:14
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin714
70.8%
Common294
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a84
11.8%
t70
9.8%
s70
9.8%
m70
9.8%
p56
 
7.8%
e56
 
7.8%
i42
 
5.9%
c42
 
5.9%
d42
 
5.9%
l28
 
3.9%
Other values (8)154
21.6%
Common
ValueCountFrequency (%)
/98
33.3%
.42
14.3%
721
 
7.1%
817
 
5.8%
916
 
5.4%
214
 
4.8%
114
 
4.8%
_14
 
4.8%
:14
 
4.8%
511
 
3.7%
Other values (4)33
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/98
 
9.7%
a84
 
8.3%
t70
 
6.9%
s70
 
6.9%
m70
 
6.9%
p56
 
5.6%
e56
 
5.6%
i42
 
4.2%
c42
 
4.2%
.42
 
4.2%
Other values (22)378
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct14
Distinct (%)100.0%
Missing67
Missing (%)82.7%
Memory size776.0 B
https://static.tvmaze.com/uploads/images/original_untouched/360/901421.jpg
https://static.tvmaze.com/uploads/images/original_untouched/286/715106.jpg
https://static.tvmaze.com/uploads/images/original_untouched/293/734764.jpg
https://static.tvmaze.com/uploads/images/original_untouched/286/715360.jpg
https://static.tvmaze.com/uploads/images/original_untouched/286/715179.jpg
Other values (9)

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters1036
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/360/901421.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715106.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/293/734764.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715360.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/286/715179.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901421.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/286/715106.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/293/734764.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/286/715360.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/286/715179.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/340/850668.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719897.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719898.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719899.jpg1
 
1.2%
https://static.tvmaze.com/uploads/images/original_untouched/287/719900.jpg1
 
1.2%
Other values (4)4
 
4.9%
(Missing)67
82.7%

Length

2022-09-05T21:36:14.698229image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901421.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/286/715106.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/293/734764.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/286/715360.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/286/715179.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/340/850668.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719897.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719898.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719899.jpg1
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/719900.jpg1
 
7.1%
Other values (4)4
28.6%

Most occurring characters

ValueCountFrequency (%)
/98
 
9.5%
t84
 
8.1%
a70
 
6.8%
s56
 
5.4%
i56
 
5.4%
o56
 
5.4%
p42
 
4.1%
c42
 
4.1%
.42
 
4.1%
g42
 
4.1%
Other values (23)448
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter742
71.6%
Other Punctuation154
 
14.9%
Decimal Number126
 
12.2%
Connector Punctuation14
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t84
 
11.3%
a70
 
9.4%
s56
 
7.5%
i56
 
7.5%
o56
 
7.5%
p42
 
5.7%
c42
 
5.7%
g42
 
5.7%
m42
 
5.7%
e42
 
5.7%
Other values (9)210
28.3%
Decimal Number
ValueCountFrequency (%)
721
16.7%
817
13.5%
916
12.7%
114
11.1%
214
11.1%
511
8.7%
610
7.9%
09
7.1%
38
 
6.3%
46
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/98
63.6%
.42
27.3%
:14
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin742
71.6%
Common294
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t84
 
11.3%
a70
 
9.4%
s56
 
7.5%
i56
 
7.5%
o56
 
7.5%
p42
 
5.7%
c42
 
5.7%
g42
 
5.7%
m42
 
5.7%
e42
 
5.7%
Other values (9)210
28.3%
Common
ValueCountFrequency (%)
/98
33.3%
.42
14.3%
721
 
7.1%
817
 
5.8%
916
 
5.4%
:14
 
4.8%
_14
 
4.8%
114
 
4.8%
214
 
4.8%
511
 
3.7%
Other values (4)33
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII1036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/98
 
9.5%
t84
 
8.1%
a70
 
6.8%
s56
 
5.4%
i56
 
5.4%
o56
 
5.4%
p42
 
4.1%
c42
 
4.1%
.42
 
4.1%
g42
 
4.1%
Other values (23)448
43.2%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size776.0 B
https://api.tvmaze.com/episodes/1972782
 
1
https://api.tvmaze.com/episodes/2001104
 
1
https://api.tvmaze.com/episodes/1977633
 
1
https://api.tvmaze.com/episodes/1977632
 
1
https://api.tvmaze.com/episodes/1976186
 
1
Other values (76)
76 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3159
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1972782
2nd rowhttps://api.tvmaze.com/episodes/1979223
3rd rowhttps://api.tvmaze.com/episodes/1971567
4th rowhttps://api.tvmaze.com/episodes/1983072
5th rowhttps://api.tvmaze.com/episodes/2386103

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19727821
 
1.2%
https://api.tvmaze.com/episodes/20011041
 
1.2%
https://api.tvmaze.com/episodes/19776331
 
1.2%
https://api.tvmaze.com/episodes/19776321
 
1.2%
https://api.tvmaze.com/episodes/19761861
 
1.2%
https://api.tvmaze.com/episodes/19761851
 
1.2%
https://api.tvmaze.com/episodes/19761551
 
1.2%
https://api.tvmaze.com/episodes/19761541
 
1.2%
https://api.tvmaze.com/episodes/19761371
 
1.2%
https://api.tvmaze.com/episodes/19761361
 
1.2%
Other values (71)71
87.7%

Length

2022-09-05T21:36:14.778584image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19727821
 
1.2%
https://api.tvmaze.com/episodes/19792231
 
1.2%
https://api.tvmaze.com/episodes/19715671
 
1.2%
https://api.tvmaze.com/episodes/19830721
 
1.2%
https://api.tvmaze.com/episodes/23861031
 
1.2%
https://api.tvmaze.com/episodes/19856151
 
1.2%
https://api.tvmaze.com/episodes/20300181
 
1.2%
https://api.tvmaze.com/episodes/19735401
 
1.2%
https://api.tvmaze.com/episodes/19735411
 
1.2%
https://api.tvmaze.com/episodes/20663671
 
1.2%
Other values (71)71
87.7%

Most occurring characters

ValueCountFrequency (%)
/324
 
10.3%
p243
 
7.7%
s243
 
7.7%
e243
 
7.7%
t243
 
7.7%
o162
 
5.1%
a162
 
5.1%
i162
 
5.1%
.162
 
5.1%
m162
 
5.1%
Other values (16)1053
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2025
64.1%
Other Punctuation567
 
17.9%
Decimal Number567
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p243
12.0%
s243
12.0%
e243
12.0%
t243
12.0%
o162
8.0%
a162
8.0%
i162
8.0%
m162
8.0%
h81
 
4.0%
d81
 
4.0%
Other values (3)243
12.0%
Decimal Number
ValueCountFrequency (%)
1106
18.7%
987
15.3%
764
11.3%
258
10.2%
851
9.0%
050
8.8%
649
8.6%
538
 
6.7%
337
 
6.5%
427
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/324
57.1%
.162
28.6%
:81
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2025
64.1%
Common1134
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/324
28.6%
.162
14.3%
1106
 
9.3%
987
 
7.7%
:81
 
7.1%
764
 
5.6%
258
 
5.1%
851
 
4.5%
050
 
4.4%
649
 
4.3%
Other values (3)102
 
9.0%
Latin
ValueCountFrequency (%)
p243
12.0%
s243
12.0%
e243
12.0%
t243
12.0%
o162
8.0%
a162
8.0%
i162
8.0%
m162
8.0%
h81
 
4.0%
d81
 
4.0%
Other values (3)243
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/324
 
10.3%
p243
 
7.7%
s243
 
7.7%
e243
 
7.7%
t243
 
7.7%
o162
 
5.1%
a162
 
5.1%
i162
 
5.1%
.162
 
5.1%
m162
 
5.1%
Other values (16)1053
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct67
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47565.06173
Minimum2266
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:14.877890image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2266
5-th percentile26268
Q146139
median51870
Q352250
95-th percentile57953
Maximum61755
Range59489
Interquartile range (IQR)6111

Descriptive statistics

Standard deviation11243.77473
Coefficient of variation (CV)0.2363872624
Kurtosis5.811283344
Mean47565.06173
Median Absolute Deviation (MAD)2723
Skewness-2.26475712
Sum3852770
Variance126422470.2
MonotonicityNot monotonic
2022-09-05T21:36:14.987197image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
519274
 
4.9%
521042
 
2.5%
521082
 
2.5%
524212
 
2.5%
521592
 
2.5%
527802
 
2.5%
518702
 
2.5%
520382
 
2.5%
570302
 
2.5%
586892
 
2.5%
Other values (57)59
72.8%
ValueCountFrequency (%)
22661
1.2%
25041
1.2%
152501
1.2%
249631
1.2%
262681
1.2%
270551
1.2%
283461
1.2%
306061
1.2%
336911
1.2%
339441
1.2%
ValueCountFrequency (%)
617551
1.2%
595551
1.2%
586892
2.5%
579531
1.2%
576891
1.2%
574781
1.2%
570302
2.5%
567461
1.2%
565311
1.2%
560641
1.2%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size776.0 B
https://www.tvmaze.com/shows/51927/alien-worlds
 
4
https://www.tvmaze.com/shows/52104/twisted-fate-of-love
 
2
https://www.tvmaze.com/shows/52108/psych-hunter
 
2
https://www.tvmaze.com/shows/52421/you-complete-me
 
2
https://www.tvmaze.com/shows/52159/to-love
 
2
Other values (62)
69 

Length

Max length73
Median length61
Mean length50.87654321
Min length41

Characters and Unicode

Total characters4121
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)67.9%

Sample

1st rowhttps://www.tvmaze.com/shows/49630/kontakty
2nd rowhttps://www.tvmaze.com/shows/52198/kotiki
3rd rowhttps://www.tvmaze.com/shows/47207/mermaid-prince
4th rowhttps://www.tvmaze.com/shows/48395/wan-sheng-jie
5th rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/51927/alien-worlds4
 
4.9%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.5%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.5%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.5%
https://www.tvmaze.com/shows/52159/to-love2
 
2.5%
https://www.tvmaze.com/shows/52780/mermaid-prince2
 
2.5%
https://www.tvmaze.com/shows/51870/something-just-like-this2
 
2.5%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.5%
https://www.tvmaze.com/shows/57030/gjor-det-sjol2
 
2.5%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
2.5%
Other values (57)59
72.8%

Length

2022-09-05T21:36:15.094190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/51927/alien-worlds4
 
4.9%
https://www.tvmaze.com/shows/51870/something-just-like-this2
 
2.5%
https://www.tvmaze.com/shows/52107/new-face2
 
2.5%
https://www.tvmaze.com/shows/52106/insect-detective2
 
2.5%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
2.5%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.5%
https://www.tvmaze.com/shows/57030/gjor-det-sjol2
 
2.5%
https://www.tvmaze.com/shows/52780/mermaid-prince2
 
2.5%
https://www.tvmaze.com/shows/52159/to-love2
 
2.5%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
2.5%
Other values (57)59
72.8%

Most occurring characters

ValueCountFrequency (%)
/405
 
9.8%
w353
 
8.6%
t328
 
8.0%
s325
 
7.9%
o245
 
5.9%
e221
 
5.4%
m202
 
4.9%
h202
 
4.9%
.162
 
3.9%
a161
 
3.9%
Other values (29)1517
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2915
70.7%
Other Punctuation648
 
15.7%
Decimal Number408
 
9.9%
Dash Punctuation150
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w353
12.1%
t328
11.3%
s325
11.1%
o245
 
8.4%
e221
 
7.6%
m202
 
6.9%
h202
 
6.9%
a161
 
5.5%
c111
 
3.8%
p106
 
3.6%
Other values (15)661
22.7%
Decimal Number
ValueCountFrequency (%)
573
17.9%
449
12.0%
145
11.0%
244
10.8%
037
9.1%
635
8.6%
735
8.6%
933
8.1%
331
7.6%
826
 
6.4%
Other Punctuation
ValueCountFrequency (%)
/405
62.5%
.162
 
25.0%
:81
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2915
70.7%
Common1206
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w353
12.1%
t328
11.3%
s325
11.1%
o245
 
8.4%
e221
 
7.6%
m202
 
6.9%
h202
 
6.9%
a161
 
5.5%
c111
 
3.8%
p106
 
3.6%
Other values (15)661
22.7%
Common
ValueCountFrequency (%)
/405
33.6%
.162
 
13.4%
-150
 
12.4%
:81
 
6.7%
573
 
6.1%
449
 
4.1%
145
 
3.7%
244
 
3.6%
037
 
3.1%
635
 
2.9%
Other values (4)125
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/405
 
9.8%
w353
 
8.6%
t328
 
8.0%
s325
 
7.9%
o245
 
5.9%
e221
 
5.4%
m202
 
4.9%
h202
 
4.9%
.162
 
3.9%
a161
 
3.9%
Other values (29)1517
36.8%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct66
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size776.0 B
Alien Worlds
 
4
Mermaid Prince
 
3
New Face
 
2
You Complete Me
 
2
To Love
 
2
Other values (61)
68 

Length

Max length40
Median length27
Mean length16.16049383
Min length6

Characters and Unicode

Total characters1309
Distinct characters93
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)66.7%

Sample

1st rowКонтакты
2nd rowКотики
3rd rowMermaid Prince
4th rowWan Sheng Jie
5th rowXian Feng Jian Yu Lu

Common Values

ValueCountFrequency (%)
Alien Worlds4
 
4.9%
Mermaid Prince3
 
3.7%
New Face2
 
2.5%
You Complete Me2
 
2.5%
To Love2
 
2.5%
Psych Hunter2
 
2.5%
Please Wait, Brother2
 
2.5%
Something Just Like This2
 
2.5%
Gjør det sjøl2
 
2.5%
My Supernatural Power2
 
2.5%
Other values (56)58
71.6%

Length

2022-09-05T21:36:15.197939image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the6
 
2.6%
worlds4
 
1.7%
love4
 
1.7%
alien4
 
1.7%
new3
 
1.3%
you3
 
1.3%
prince3
 
1.3%
mermaid3
 
1.3%
yi3
 
1.3%
of3
 
1.3%
Other values (168)196
84.5%

Most occurring characters

ValueCountFrequency (%)
151
 
11.5%
e127
 
9.7%
i66
 
5.0%
a62
 
4.7%
n62
 
4.7%
o60
 
4.6%
r57
 
4.4%
s54
 
4.1%
t53
 
4.0%
l45
 
3.4%
Other values (83)572
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter924
70.6%
Uppercase Letter211
 
16.1%
Space Separator151
 
11.5%
Other Punctuation18
 
1.4%
Decimal Number5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e127
13.7%
i66
 
7.1%
a62
 
6.7%
n62
 
6.7%
o60
 
6.5%
r57
 
6.2%
s54
 
5.8%
t53
 
5.7%
l45
 
4.9%
h35
 
3.8%
Other values (42)303
32.8%
Uppercase Letter
ValueCountFrequency (%)
T23
 
10.9%
S20
 
9.5%
W16
 
7.6%
M15
 
7.1%
C11
 
5.2%
P11
 
5.2%
A10
 
4.7%
F9
 
4.3%
Y9
 
4.3%
L9
 
4.3%
Other values (22)78
37.0%
Other Punctuation
ValueCountFrequency (%)
:5
27.8%
'5
27.8%
.4
22.2%
,3
16.7%
&1
 
5.6%
Decimal Number
ValueCountFrequency (%)
02
40.0%
22
40.0%
11
20.0%
Space Separator
ValueCountFrequency (%)
151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1021
78.0%
Common174
 
13.3%
Cyrillic114
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e127
 
12.4%
i66
 
6.5%
a62
 
6.1%
n62
 
6.1%
o60
 
5.9%
r57
 
5.6%
s54
 
5.3%
t53
 
5.2%
l45
 
4.4%
h35
 
3.4%
Other values (40)400
39.2%
Cyrillic
ValueCountFrequency (%)
о13
 
11.4%
р10
 
8.8%
к9
 
7.9%
т9
 
7.9%
е8
 
7.0%
а7
 
6.1%
и7
 
6.1%
м5
 
4.4%
н5
 
4.4%
с5
 
4.4%
Other values (24)36
31.6%
Common
ValueCountFrequency (%)
151
86.8%
:5
 
2.9%
'5
 
2.9%
.4
 
2.3%
,3
 
1.7%
02
 
1.1%
22
 
1.1%
11
 
0.6%
&1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1188
90.8%
Cyrillic114
 
8.7%
None7
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
151
 
12.7%
e127
 
10.7%
i66
 
5.6%
a62
 
5.2%
n62
 
5.2%
o60
 
5.1%
r57
 
4.8%
s54
 
4.5%
t53
 
4.5%
l45
 
3.8%
Other values (48)451
38.0%
Cyrillic
ValueCountFrequency (%)
о13
 
11.4%
р10
 
8.8%
к9
 
7.9%
т9
 
7.9%
е8
 
7.0%
а7
 
6.1%
и7
 
6.1%
м5
 
4.4%
н5
 
4.4%
с5
 
4.4%
Other values (24)36
31.6%
None
ValueCountFrequency (%)
ø7
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size776.0 B
Scripted
33 
Talk Show
12 
Animation
10 
Reality
Documentary
Other values (5)

Length

Max length11
Median length10
Mean length8.395061728
Min length4

Characters and Unicode

Total characters680
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.5%

Sample

1st rowGame Show
2nd rowScripted
3rd rowScripted
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted33
40.7%
Talk Show12
 
14.8%
Animation10
 
12.3%
Reality9
 
11.1%
Documentary8
 
9.9%
Game Show3
 
3.7%
Variety2
 
2.5%
Sports2
 
2.5%
Award Show1
 
1.2%
News1
 
1.2%

Length

2022-09-05T21:36:15.293979image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:15.406695image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted33
34.0%
show16
16.5%
talk12
 
12.4%
animation10
 
10.3%
reality9
 
9.3%
documentary8
 
8.2%
game3
 
3.1%
variety2
 
2.1%
sports2
 
2.1%
award1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
i64
 
9.4%
t64
 
9.4%
e56
 
8.2%
S51
 
7.5%
r46
 
6.8%
a45
 
6.6%
c41
 
6.0%
o36
 
5.3%
p35
 
5.1%
d34
 
5.0%
Other values (17)208
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter567
83.4%
Uppercase Letter97
 
14.3%
Space Separator16
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i64
11.3%
t64
11.3%
e56
9.9%
r46
 
8.1%
a45
 
7.9%
c41
 
7.2%
o36
 
6.3%
p35
 
6.2%
d34
 
6.0%
n28
 
4.9%
Other values (8)118
20.8%
Uppercase Letter
ValueCountFrequency (%)
S51
52.6%
T12
 
12.4%
A11
 
11.3%
R9
 
9.3%
D8
 
8.2%
G3
 
3.1%
V2
 
2.1%
N1
 
1.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin664
97.6%
Common16
 
2.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i64
 
9.6%
t64
 
9.6%
e56
 
8.4%
S51
 
7.7%
r46
 
6.9%
a45
 
6.8%
c41
 
6.2%
o36
 
5.4%
p35
 
5.3%
d34
 
5.1%
Other values (16)192
28.9%
Common
ValueCountFrequency (%)
16
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII680
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i64
 
9.4%
t64
 
9.4%
e56
 
8.2%
S51
 
7.5%
r46
 
6.8%
a45
 
6.6%
c41
 
6.0%
o36
 
5.3%
p35
 
5.1%
d34
 
5.0%
Other values (17)208
30.6%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct16
Distinct (%)20.0%
Missing1
Missing (%)1.2%
Memory size776.0 B
Chinese
26 
English
22 
Russian
Norwegian
Arabic
Other values (11)
14 

Length

Max length10
Median length7
Mean length7.125
Min length4

Characters and Unicode

Total characters570
Distinct characters33
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)11.2%

Sample

1st rowRussian
2nd rowRussian
3rd rowKorean
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese26
32.1%
English22
27.2%
Russian8
 
9.9%
Norwegian7
 
8.6%
Arabic3
 
3.7%
Korean3
 
3.7%
Japanese2
 
2.5%
Ukrainian1
 
1.2%
Portuguese1
 
1.2%
French1
 
1.2%
Other values (6)6
 
7.4%

Length

2022-09-05T21:36:15.501865image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese26
32.5%
english22
27.5%
russian8
 
10.0%
norwegian7
 
8.8%
arabic3
 
3.8%
korean3
 
3.8%
japanese2
 
2.5%
ukrainian1
 
1.2%
portuguese1
 
1.2%
french1
 
1.2%
Other values (6)6
 
7.5%

Most occurring characters

ValueCountFrequency (%)
n74
13.0%
i72
12.6%
e70
12.3%
s69
12.1%
h54
9.5%
a33
 
5.8%
g31
 
5.4%
C26
 
4.6%
E22
 
3.9%
l22
 
3.9%
Other values (23)97
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter490
86.0%
Uppercase Letter80
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n74
15.1%
i72
14.7%
e70
14.3%
s69
14.1%
h54
11.0%
a33
6.7%
g31
6.3%
l22
 
4.5%
r17
 
3.5%
u12
 
2.4%
Other values (9)36
7.3%
Uppercase Letter
ValueCountFrequency (%)
C26
32.5%
E22
27.5%
R8
 
10.0%
N7
 
8.8%
K4
 
5.0%
A3
 
3.8%
J2
 
2.5%
S2
 
2.5%
U1
 
1.2%
P1
 
1.2%
Other values (4)4
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
Latin570
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n74
13.0%
i72
12.6%
e70
12.3%
s69
12.1%
h54
9.5%
a33
 
5.8%
g31
 
5.4%
C26
 
4.6%
E22
 
3.9%
l22
 
3.9%
Other values (23)97
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n74
13.0%
i72
12.6%
e70
12.3%
s69
12.1%
h54
9.5%
a33
 
5.8%
g31
 
5.4%
C26
 
4.6%
E22
 
3.9%
l22
 
3.9%
Other values (23)97
17.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size776.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size776.0 B
Running
43 
Ended
35 
To Be Determined
 
3

Length

Max length16
Median length7
Mean length6.469135802
Min length5

Characters and Unicode

Total characters524
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running43
53.1%
Ended35
43.2%
To Be Determined3
 
3.7%

Length

2022-09-05T21:36:15.587500image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:15.674833image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running43
49.4%
ended35
40.2%
to3
 
3.4%
be3
 
3.4%
determined3
 
3.4%

Most occurring characters

ValueCountFrequency (%)
n167
31.9%
d73
13.9%
e47
 
9.0%
i46
 
8.8%
R43
 
8.2%
u43
 
8.2%
g43
 
8.2%
E35
 
6.7%
6
 
1.1%
T3
 
0.6%
Other values (6)18
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter431
82.3%
Uppercase Letter87
 
16.6%
Space Separator6
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n167
38.7%
d73
16.9%
e47
 
10.9%
i46
 
10.7%
u43
 
10.0%
g43
 
10.0%
o3
 
0.7%
t3
 
0.7%
r3
 
0.7%
m3
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
R43
49.4%
E35
40.2%
T3
 
3.4%
B3
 
3.4%
D3
 
3.4%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin518
98.9%
Common6
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n167
32.2%
d73
14.1%
e47
 
9.1%
i46
 
8.9%
R43
 
8.3%
u43
 
8.3%
g43
 
8.3%
E35
 
6.8%
T3
 
0.6%
o3
 
0.6%
Other values (5)15
 
2.9%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII524
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n167
31.9%
d73
13.9%
e47
 
9.0%
i46
 
8.8%
R43
 
8.2%
u43
 
8.2%
g43
 
8.2%
E35
 
6.7%
6
 
1.1%
T3
 
0.6%
Other values (6)18
 
3.4%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct22
Distinct (%)36.1%
Missing20
Missing (%)24.7%
Infinite0
Infinite (%)0.0%
Mean43.06557377
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:15.748803image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q120
median40
Q345
95-th percentile120
Maximum300
Range298
Interquartile range (IQR)25

Descriptive statistics

Standard deviation42.39570295
Coefficient of variation (CV)0.9844453292
Kurtosis22.45864587
Mean43.06557377
Median Absolute Deviation (MAD)10
Skewness4.064178305
Sum2627
Variance1797.395628
MonotonicityNot monotonic
2022-09-05T21:36:15.843829image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
4519
23.5%
305
 
6.2%
205
 
6.2%
603
 
3.7%
1203
 
3.7%
253
 
3.7%
53
 
3.7%
372
 
2.5%
82
 
2.5%
122
 
2.5%
Other values (12)14
17.3%
(Missing)20
24.7%
ValueCountFrequency (%)
21
 
1.2%
41
 
1.2%
53
3.7%
82
 
2.5%
122
 
2.5%
151
 
1.2%
191
 
1.2%
205
6.2%
231
 
1.2%
253
3.7%
ValueCountFrequency (%)
3001
 
1.2%
1203
 
3.7%
902
 
2.5%
603
 
3.7%
551
 
1.2%
4519
23.5%
402
 
2.5%
372
 
2.5%
351
 
1.2%
331
 
1.2%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct37
Distinct (%)48.1%
Missing4
Missing (%)4.9%
Infinite0
Infinite (%)0.0%
Mean38.03896104
Minimum2
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:15.937978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q115
median37
Q345
95-th percentile91.6
Maximum300
Range298
Interquartile range (IQR)30

Descriptive statistics

Standard deviation38.37571928
Coefficient of variation (CV)1.008852982
Kurtosis28.53561808
Mean38.03896104
Median Absolute Deviation (MAD)12
Skewness4.485326264
Sum2929
Variance1472.69583
MonotonicityNot monotonic
2022-09-05T21:36:16.045098image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
4518
22.2%
55
 
6.2%
254
 
4.9%
444
 
4.9%
373
 
3.7%
303
 
3.7%
203
 
3.7%
602
 
2.5%
122
 
2.5%
112
 
2.5%
Other values (27)31
38.3%
(Missing)4
 
4.9%
ValueCountFrequency (%)
21
 
1.2%
41
 
1.2%
55
6.2%
61
 
1.2%
72
 
2.5%
81
 
1.2%
91
 
1.2%
112
 
2.5%
122
 
2.5%
131
 
1.2%
ValueCountFrequency (%)
3001
 
1.2%
1201
 
1.2%
1101
 
1.2%
981
 
1.2%
901
 
1.2%
771
 
1.2%
602
 
2.5%
591
 
1.2%
541
 
1.2%
4518
22.2%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct61
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size776.0 B
2020-12-02
 
6
2020-11-23
 
4
2020-11-18
 
3
2020-11-25
 
2
2020-07-08
 
2
Other values (56)
64 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters810
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)59.3%

Sample

1st row2019-04-03
2nd row2020-11-30
3rd row2020-04-14
4th row2020-04-01
5th row2020-07-11

Common Values

ValueCountFrequency (%)
2020-12-026
 
7.4%
2020-11-234
 
4.9%
2020-11-183
 
3.7%
2020-11-252
 
2.5%
2020-07-082
 
2.5%
2020-11-302
 
2.5%
2020-11-082
 
2.5%
2020-10-072
 
2.5%
2020-11-172
 
2.5%
2020-11-032
 
2.5%
Other values (51)54
66.7%

Length

2022-09-05T21:36:16.132851image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-026
 
7.4%
2020-11-234
 
4.9%
2020-11-183
 
3.7%
2020-11-172
 
2.5%
2020-11-042
 
2.5%
2020-11-242
 
2.5%
2020-11-032
 
2.5%
2020-11-192
 
2.5%
2020-10-072
 
2.5%
2020-11-082
 
2.5%
Other values (51)54
66.7%

Most occurring characters

ValueCountFrequency (%)
0214
26.4%
2174
21.5%
-162
20.0%
1140
17.3%
928
 
3.5%
422
 
2.7%
821
 
2.6%
320
 
2.5%
712
 
1.5%
511
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number648
80.0%
Dash Punctuation162
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0214
33.0%
2174
26.9%
1140
21.6%
928
 
4.3%
422
 
3.4%
821
 
3.2%
320
 
3.1%
712
 
1.9%
511
 
1.7%
66
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0214
26.4%
2174
21.5%
-162
20.0%
1140
17.3%
928
 
3.5%
422
 
2.7%
821
 
2.6%
320
 
2.5%
712
 
1.5%
511
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0214
26.4%
2174
21.5%
-162
20.0%
1140
17.3%
928
 
3.5%
422
 
2.7%
821
 
2.6%
320
 
2.5%
712
 
1.5%
511
 
1.4%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct15
Distinct (%)42.9%
Missing46
Missing (%)56.8%
Memory size776.0 B
2020-12-02
2020-12-16
2020-12-30
2020-12-08
2020-12-03
Other values (10)
13 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters350
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)20.0%

Sample

1st row2020-12-11
2nd row2020-12-10
3rd row2020-12-16
4th row2020-12-08
5th row2020-12-08

Common Values

ValueCountFrequency (%)
2020-12-028
 
9.9%
2020-12-165
 
6.2%
2020-12-305
 
6.2%
2020-12-082
 
2.5%
2020-12-032
 
2.5%
2020-12-222
 
2.5%
2020-12-232
 
2.5%
2021-01-142
 
2.5%
2020-12-111
 
1.2%
2020-12-101
 
1.2%
Other values (5)5
 
6.2%
(Missing)46
56.8%

Length

2022-09-05T21:36:16.212978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-028
22.9%
2020-12-165
14.3%
2020-12-305
14.3%
2020-12-082
 
5.7%
2020-12-032
 
5.7%
2020-12-222
 
5.7%
2020-12-232
 
5.7%
2021-01-142
 
5.7%
2020-12-111
 
2.9%
2020-12-101
 
2.9%
Other values (5)5
14.3%

Most occurring characters

ValueCountFrequency (%)
2118
33.7%
089
25.4%
-70
20.0%
150
14.3%
39
 
2.6%
65
 
1.4%
83
 
0.9%
43
 
0.9%
71
 
0.3%
51
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number280
80.0%
Dash Punctuation70
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2118
42.1%
089
31.8%
150
17.9%
39
 
3.2%
65
 
1.8%
83
 
1.1%
43
 
1.1%
71
 
0.4%
51
 
0.4%
91
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
-70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common350
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2118
33.7%
089
25.4%
-70
20.0%
150
14.3%
39
 
2.6%
65
 
1.4%
83
 
0.9%
43
 
0.9%
71
 
0.3%
51
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2118
33.7%
089
25.4%
-70
20.0%
150
14.3%
39
 
2.6%
65
 
1.4%
83
 
0.9%
43
 
0.9%
71
 
0.3%
51
 
0.3%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct59
Distinct (%)86.8%
Missing13
Missing (%)16.0%
Memory size776.0 B
https://www.netflix.com/title/80221410
 
4
https://tv.nrk.no/serie/gjoer-det-sjoel
 
2
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=
 
2
https://v.youku.com/v_show/id_XNDg2OTQ0ODAwOA==.html?s=dfbc7998206c499cac28
 
2
https://v.qq.com/detail/m/mzc00200tu76tos.html
 
2
Other values (54)
56 

Length

Max length97
Median length68
Mean length51.45588235
Min length18

Characters and Unicode

Total characters3499
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)76.5%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI
2nd rowhttp://epic-media.ru/project/kotiki
3rd rowhttps://v.qq.com/detail/a/awnia0n2erqryf3.html
4th rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html
5th rowhttps://v.qq.com/detail/w/ww18u675tfmhas6.html

Common Values

ValueCountFrequency (%)
https://www.netflix.com/title/802214104
 
4.9%
https://tv.nrk.no/serie/gjoer-det-sjoel2
 
2.5%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.5%
https://v.youku.com/v_show/id_XNDg2OTQ0ODAwOA==.html?s=dfbc7998206c499cac282
 
2.5%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.5%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.5%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.5%
https://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI1
 
1.2%
https://discoveryplus.com/no/show/jan-thomas-verden1
 
1.2%
https://elcinema.com/work/2061816/1
 
1.2%
Other values (49)49
60.5%
(Missing)13
 
16.0%

Length

2022-09-05T21:36:16.317913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/title/802214104
 
5.9%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.9%
https://v.youku.com/v_show/id_xndg2otq0odawoa==.html?s=dfbc7998206c499cac282
 
2.9%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.9%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.9%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.9%
https://tv.nrk.no/serie/gjoer-det-sjoel2
 
2.9%
https://tv.nrk.no/serie/stjernestoev1
 
1.5%
http://www.melon.com/mma/index.htm1
 
1.5%
https://salemsocial.kz/projects/orcestr1
 
1.5%
Other values (49)49
72.1%

Most occurring characters

ValueCountFrequency (%)
/279
 
8.0%
t270
 
7.7%
s184
 
5.3%
e160
 
4.6%
o159
 
4.5%
w143
 
4.1%
.136
 
3.9%
h130
 
3.7%
i110
 
3.1%
m107
 
3.1%
Other values (64)1821
52.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2270
64.9%
Other Punctuation565
 
16.1%
Decimal Number305
 
8.7%
Uppercase Letter266
 
7.6%
Dash Punctuation46
 
1.3%
Math Symbol29
 
0.8%
Connector Punctuation18
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t270
 
11.9%
s184
 
8.1%
e160
 
7.0%
o159
 
7.0%
w143
 
6.3%
h130
 
5.7%
i110
 
4.8%
m107
 
4.7%
p106
 
4.7%
c104
 
4.6%
Other values (16)797
35.1%
Uppercase Letter
ValueCountFrequency (%)
E26
 
9.8%
A22
 
8.3%
B19
 
7.1%
P15
 
5.6%
Y14
 
5.3%
L12
 
4.5%
Q11
 
4.1%
O11
 
4.1%
C11
 
4.1%
D11
 
4.1%
Other values (16)114
42.9%
Decimal Number
ValueCountFrequency (%)
048
15.7%
938
12.5%
137
12.1%
836
11.8%
234
11.1%
529
9.5%
425
8.2%
624
7.9%
720
6.6%
314
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/279
49.4%
.136
24.1%
:68
 
12.0%
%57
 
10.1%
?16
 
2.8%
&7
 
1.2%
#1
 
0.2%
!1
 
0.2%
Math Symbol
ValueCountFrequency (%)
=27
93.1%
+2
 
6.9%
Dash Punctuation
ValueCountFrequency (%)
-46
100.0%
Connector Punctuation
ValueCountFrequency (%)
_18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2536
72.5%
Common963
 
27.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t270
 
10.6%
s184
 
7.3%
e160
 
6.3%
o159
 
6.3%
w143
 
5.6%
h130
 
5.1%
i110
 
4.3%
m107
 
4.2%
p106
 
4.2%
c104
 
4.1%
Other values (42)1063
41.9%
Common
ValueCountFrequency (%)
/279
29.0%
.136
14.1%
:68
 
7.1%
%57
 
5.9%
048
 
5.0%
-46
 
4.8%
938
 
3.9%
137
 
3.8%
836
 
3.7%
234
 
3.5%
Other values (12)184
19.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/279
 
8.0%
t270
 
7.7%
s184
 
5.3%
e160
 
4.6%
o159
 
4.5%
w143
 
4.1%
.136
 
3.9%
h130
 
3.7%
i110
 
3.1%
m107
 
3.1%
Other values (64)1821
52.0%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size776.0 B
47 
20:00
13 
10:00
12:00
 
3
06:00
 
2
Other values (8)
11 

Length

Max length5
Median length0
Mean length2.098765432
Min length0

Characters and Unicode

Total characters170
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)6.2%

Sample

1st row
2nd row10:00
3rd row11:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
47
58.0%
20:0013
 
16.0%
10:005
 
6.2%
12:003
 
3.7%
06:002
 
2.5%
21:002
 
2.5%
00:002
 
2.5%
19:002
 
2.5%
11:001
 
1.2%
17:351
 
1.2%
Other values (3)3
 
3.7%

Length

2022-09-05T21:36:16.411920image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0013
38.2%
10:005
 
14.7%
12:003
 
8.8%
06:002
 
5.9%
21:002
 
5.9%
00:002
 
5.9%
19:002
 
5.9%
11:001
 
2.9%
17:351
 
2.9%
18:001
 
2.9%
Other values (2)2
 
5.9%

Most occurring characters

ValueCountFrequency (%)
088
51.8%
:34
 
20.0%
220
 
11.8%
118
 
10.6%
53
 
1.8%
62
 
1.2%
92
 
1.2%
71
 
0.6%
31
 
0.6%
81
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number136
80.0%
Other Punctuation34
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
088
64.7%
220
 
14.7%
118
 
13.2%
53
 
2.2%
62
 
1.5%
92
 
1.5%
71
 
0.7%
31
 
0.7%
81
 
0.7%
Other Punctuation
ValueCountFrequency (%)
:34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common170
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
088
51.8%
:34
 
20.0%
220
 
11.8%
118
 
10.6%
53
 
1.8%
62
 
1.2%
92
 
1.2%
71
 
0.6%
31
 
0.6%
81
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
088
51.8%
:34
 
20.0%
220
 
11.8%
118
 
10.6%
53
 
1.8%
62
 
1.2%
92
 
1.2%
71
 
0.6%
31
 
0.6%
81
 
0.6%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size776.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)33.3%
Missing75
Missing (%)92.6%
Memory size776.0 B
7.7
7.2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7.2
2nd row7.7
3rd row7.7
4th row7.7
5th row7.7

Common Values

ValueCountFrequency (%)
7.74
 
4.9%
7.22
 
2.5%
(Missing)75
92.6%

Length

2022-09-05T21:36:16.488514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:16.565798image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.74
66.7%
7.22
33.3%

Most occurring characters

ValueCountFrequency (%)
710
55.6%
.6
33.3%
22
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
66.7%
Other Punctuation6
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
710
83.3%
22
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
710
55.6%
.6
33.3%
22
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
710
55.6%
.6
33.3%
22
 
11.1%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.72839506
Minimum3
Maximum92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:16.647904image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6
Q114
median22
Q332
95-th percentile78
Maximum92
Range89
Interquartile range (IQR)18

Descriptive statistics

Standard deviation21.08317596
Coefficient of variation (CV)0.760346061
Kurtosis1.425163199
Mean27.72839506
Median Absolute Deviation (MAD)9
Skewness1.40511905
Sum2246
Variance444.5003086
MonotonicityNot monotonic
2022-09-05T21:36:16.746316image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
215
 
6.2%
75
 
6.2%
245
 
6.2%
224
 
4.9%
204
 
4.9%
584
 
4.9%
163
 
3.7%
303
 
3.7%
313
 
3.7%
43
 
3.7%
Other values (30)42
51.9%
ValueCountFrequency (%)
31
 
1.2%
43
3.7%
62
 
2.5%
75
6.2%
82
 
2.5%
91
 
1.2%
101
 
1.2%
112
 
2.5%
121
 
1.2%
132
 
2.5%
ValueCountFrequency (%)
921
 
1.2%
861
 
1.2%
831
 
1.2%
801
 
1.2%
781
 
1.2%
741
 
1.2%
621
 
1.2%
591
 
1.2%
584
4.9%
561
 
1.2%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct31
Distinct (%)39.2%
Missing2
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean123.0253165
Minimum1
Maximum510
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:16.835450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.6
Q121
median104
Q3182
95-th percentile379.1
Maximum510
Range509
Interquartile range (IQR)161

Descriptive statistics

Standard deviation121.5534044
Coefficient of variation (CV)0.9880356978
Kurtosis1.297827959
Mean123.0253165
Median Absolute Deviation (MAD)83
Skewness1.362738959
Sum9719
Variance14775.23012
MonotonicityNot monotonic
2022-09-05T21:36:16.936572image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
2119
23.5%
10413
16.0%
1185
 
6.2%
14
 
4.9%
2384
 
4.9%
674
 
4.9%
512
 
2.5%
2262
 
2.5%
152
 
2.5%
3272
 
2.5%
Other values (21)22
27.2%
ValueCountFrequency (%)
14
 
4.9%
152
 
2.5%
201
 
1.2%
2119
23.5%
301
 
1.2%
512
 
2.5%
541
 
1.2%
674
 
4.9%
831
 
1.2%
881
 
1.2%
ValueCountFrequency (%)
5101
 
1.2%
4581
 
1.2%
4521
 
1.2%
3801
 
1.2%
3792
2.5%
3272
2.5%
3111
 
1.2%
2741
 
1.2%
2401
 
1.2%
2384
4.9%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct31
Distinct (%)39.2%
Missing2
Missing (%)2.5%
Memory size776.0 B
YouTube
19 
Tencent QQ
13 
Youku
Netflix
NRK TV
Other values (26)
34 

Length

Max length17
Median length14
Mean length7.873417722
Min length4

Characters and Unicode

Total characters622
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)25.3%

Sample

1st rowYouTube
2nd rowEpic Media
3rd rowSeezn
4th rowTencent QQ
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube19
23.5%
Tencent QQ13
16.0%
Youku5
 
6.2%
Netflix4
 
4.9%
NRK TV4
 
4.9%
iQIYI4
 
4.9%
Bilibili2
 
2.5%
Mango TV2
 
2.5%
WWE Network2
 
2.5%
TV 2 Play2
 
2.5%
Other values (21)22
27.2%

Length

2022-09-05T21:36:17.030422image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube19
16.8%
qq13
 
11.5%
tencent13
 
11.5%
tv9
 
8.0%
youku5
 
4.4%
netflix4
 
3.5%
nrk4
 
3.5%
iqiyi4
 
3.5%
22
 
1.8%
watch2
 
1.8%
Other values (32)38
33.6%

Most occurring characters

ValueCountFrequency (%)
e65
 
10.5%
u56
 
9.0%
T44
 
7.1%
o39
 
6.3%
n34
 
5.5%
34
 
5.5%
Q30
 
4.8%
t28
 
4.5%
Y28
 
4.5%
b26
 
4.2%
Other values (42)238
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter392
63.0%
Uppercase Letter190
30.5%
Space Separator34
 
5.5%
Decimal Number2
 
0.3%
Math Symbol2
 
0.3%
Other Punctuation2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e65
16.6%
u56
14.3%
o39
9.9%
n34
8.7%
t28
7.1%
b26
 
6.6%
i25
 
6.4%
c19
 
4.8%
l17
 
4.3%
a17
 
4.3%
Other values (14)66
16.8%
Uppercase Letter
ValueCountFrequency (%)
T44
23.2%
Q30
15.8%
Y28
14.7%
N14
 
7.4%
V12
 
6.3%
W11
 
5.8%
I10
 
5.3%
P6
 
3.2%
R5
 
2.6%
E4
 
2.1%
Other values (13)26
13.7%
Other Punctuation
ValueCountFrequency (%)
!1
50.0%
.1
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin582
93.6%
Common40
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e65
 
11.2%
u56
 
9.6%
T44
 
7.6%
o39
 
6.7%
n34
 
5.8%
Q30
 
5.2%
t28
 
4.8%
Y28
 
4.8%
b26
 
4.5%
i25
 
4.3%
Other values (37)207
35.6%
Common
ValueCountFrequency (%)
34
85.0%
22
 
5.0%
+2
 
5.0%
!1
 
2.5%
.1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII622
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e65
 
10.5%
u56
 
9.0%
T44
 
7.1%
o39
 
6.3%
n34
 
5.5%
34
 
5.5%
Q30
 
4.8%
t28
 
4.5%
Y28
 
4.5%
b26
 
4.2%
Other values (42)238
38.3%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)24.5%
Missing32
Missing (%)39.5%
Memory size776.0 B
https://www.youtube.com
19 
https://v.qq.com/
13 
https://www.iq.com/
https://www.netflix.com/
https://w.mgtv.com/
Other values (7)

Length

Max length34
Median length30
Mean length21.6122449
Min length17

Characters and Unicode

Total characters1059
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)14.3%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://www.seezntv.com/
3rd rowhttps://v.qq.com/
4th rowhttps://v.qq.com/
5th rowhttps://v.qq.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com19
23.5%
https://v.qq.com/13
16.0%
https://www.iq.com/4
 
4.9%
https://www.netflix.com/4
 
4.9%
https://w.mgtv.com/2
 
2.5%
https://www.seezntv.com/1
 
1.2%
https://www.melon.com/tv/index.htm1
 
1.2%
http://www.wowpresentsplus.com1
 
1.2%
https://www.linetv.tw/1
 
1.2%
https://www.discoveryplus.com/1
 
1.2%
Other values (2)2
 
2.5%
(Missing)32
39.5%

Length

2022-09-05T21:36:17.122703image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com19
38.8%
https://v.qq.com13
26.5%
https://www.iq.com4
 
8.2%
https://www.netflix.com4
 
8.2%
https://w.mgtv.com2
 
4.1%
https://www.seezntv.com1
 
2.0%
https://www.melon.com/tv/index.htm1
 
2.0%
http://www.wowpresentsplus.com1
 
2.0%
https://www.linetv.tw1
 
2.0%
https://www.discoveryplus.com1
 
2.0%
Other values (2)2
 
4.1%

Most occurring characters

ValueCountFrequency (%)
t131
12.4%
/128
12.1%
w104
 
9.8%
.99
 
9.3%
o71
 
6.7%
s55
 
5.2%
p54
 
5.1%
m53
 
5.0%
h50
 
4.7%
c49
 
4.6%
Other values (17)265
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter783
73.9%
Other Punctuation276
 
26.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t131
16.7%
w104
13.3%
o71
9.1%
s55
 
7.0%
p54
 
6.9%
m53
 
6.8%
h50
 
6.4%
c49
 
6.3%
u42
 
5.4%
e32
 
4.1%
Other values (14)142
18.1%
Other Punctuation
ValueCountFrequency (%)
/128
46.4%
.99
35.9%
:49
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Latin783
73.9%
Common276
 
26.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t131
16.7%
w104
13.3%
o71
9.1%
s55
 
7.0%
p54
 
6.9%
m53
 
6.8%
h50
 
6.4%
c49
 
6.3%
u42
 
5.4%
e32
 
4.1%
Other values (14)142
18.1%
Common
ValueCountFrequency (%)
/128
46.4%
.99
35.9%
:49
 
17.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1059
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t131
12.4%
/128
12.1%
w104
 
9.8%
.99
 
9.3%
o71
 
6.7%
s55
 
5.2%
p54
 
5.1%
m53
 
5.0%
h50
 
4.7%
c49
 
4.6%
Other values (17)265
25.0%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing79
Missing (%)97.5%
Memory size776.0 B
19056.0
25100.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row19056.0
2nd row25100.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.2%
25100.01
 
1.2%
(Missing)79
97.5%

Length

2022-09-05T21:36:17.207867image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:17.290543image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
50.0%
25100.01
50.0%

Most occurring characters

ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number12
85.7%
Other Punctuation2
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
05
41.7%
12
 
16.7%
52
 
16.7%
91
 
8.3%
61
 
8.3%
21
 
8.3%
Other Punctuation
ValueCountFrequency (%)
.2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
05
35.7%
12
 
14.3%
52
 
14.3%
.2
 
14.3%
91
 
7.1%
61
 
7.1%
21
 
7.1%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)83.0%
Missing28
Missing (%)34.6%
Infinite0
Infinite (%)0.0%
Mean363534.3019
Minimum104271
Maximum410086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:17.377615image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile273353
Q1360665
median388680
Q3392162
95-th percentile393227.2
Maximum410086
Range305815
Interquartile range (IQR)31497

Descriptive statistics

Standard deviation57293.098
Coefficient of variation (CV)0.1576002531
Kurtosis10.8927361
Mean363534.3019
Median Absolute Deviation (MAD)5365
Skewness-3.125243113
Sum19267318
Variance3282499078
MonotonicityNot monotonic
2022-09-05T21:36:17.484007image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
3918774
 
4.9%
3921622
 
2.5%
3922142
 
2.5%
3914082
 
2.5%
3923622
 
2.5%
3926792
 
2.5%
3924102
 
2.5%
3418001
 
1.2%
3744641
 
1.2%
3809751
 
1.2%
Other values (34)34
42.0%
(Missing)28
34.6%
ValueCountFrequency (%)
1042711
1.2%
1445411
1.2%
2651931
1.2%
2787931
1.2%
2906861
1.2%
3150611
1.2%
3213641
1.2%
3269621
1.2%
3366281
1.2%
3386871
1.2%
ValueCountFrequency (%)
4100861
1.2%
3952351
1.2%
3940451
1.2%
3926821
1.2%
3926792
2.5%
3926491
1.2%
3924102
2.5%
3923622
2.5%
3922142
2.5%
3921622
2.5%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct24
Distinct (%)75.0%
Missing49
Missing (%)60.5%
Memory size776.0 B
tt13464340
tt15561200
 
2
tt13568876
 
2
tt13539710
 
2
tt11384218
 
2
Other values (19)
20 

Length

Max length10
Median length10
Mean length9.71875
Min length9

Characters and Unicode

Total characters311
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)56.2%

Sample

1st rowtt13695606
2nd rowtt10960302
3rd rowtt13470370
4th rowtt13470370
5th rowtt11492320

Common Values

ValueCountFrequency (%)
tt134643404
 
4.9%
tt155612002
 
2.5%
tt135688762
 
2.5%
tt135397102
 
2.5%
tt113842182
 
2.5%
tt134703702
 
2.5%
tt124280021
 
1.2%
tt124856361
 
1.2%
tt134193261
 
1.2%
tt00965971
 
1.2%
Other values (14)14
 
17.3%
(Missing)49
60.5%

Length

2022-09-05T21:36:17.574706image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt134643404
 
12.5%
tt135688762
 
6.2%
tt135397102
 
6.2%
tt113842182
 
6.2%
tt134703702
 
6.2%
tt155612002
 
6.2%
tt109603021
 
3.1%
tt91695981
 
3.1%
tt40870321
 
3.1%
tt66189221
 
3.1%
Other values (14)14
43.8%

Most occurring characters

ValueCountFrequency (%)
t64
20.6%
143
13.8%
331
10.0%
631
10.0%
428
9.0%
028
9.0%
222
 
7.1%
820
 
6.4%
516
 
5.1%
915
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number247
79.4%
Lowercase Letter64
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
143
17.4%
331
12.6%
631
12.6%
428
11.3%
028
11.3%
222
8.9%
820
8.1%
516
 
6.5%
915
 
6.1%
713
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
t64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common247
79.4%
Latin64
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
143
17.4%
331
12.6%
631
12.6%
428
11.3%
028
11.3%
222
8.9%
820
8.1%
516
 
6.5%
915
 
6.1%
713
 
5.3%
Latin
ValueCountFrequency (%)
t64
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII311
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t64
20.6%
143
13.8%
331
10.0%
631
10.0%
428
9.0%
028
9.0%
222
 
7.1%
820
 
6.4%
516
 
5.1%
915
 
4.8%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct60
Distinct (%)81.1%
Missing7
Missing (%)8.6%
Memory size776.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/287/719881.jpg
 
4
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg
 
2
Other values (55)
62 

Length

Max length72
Median length71
Mean length71.04054054
Min length70

Characters and Unicode

Total characters5257
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)64.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/283/709704.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/259/648137.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/287/719881.jpg4
 
4.9%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729458.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713076.jpg2
 
2.5%
Other values (50)52
64.2%
(Missing)7
 
8.6%

Length

2022-09-05T21:36:17.661166image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/287/719881.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713076.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/288/720951.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/350/877137.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721821.jpg2
 
2.7%
Other values (50)52
70.3%

Most occurring characters

ValueCountFrequency (%)
t518
 
9.9%
/518
 
9.9%
a370
 
7.0%
m370
 
7.0%
p296
 
5.6%
s296
 
5.6%
i296
 
5.6%
.222
 
4.2%
e222
 
4.2%
o222
 
4.2%
Other values (22)1927
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3700
70.4%
Other Punctuation814
 
15.5%
Decimal Number669
 
12.7%
Connector Punctuation74
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t518
14.0%
a370
10.0%
m370
10.0%
p296
 
8.0%
s296
 
8.0%
i296
 
8.0%
e222
 
6.0%
o222
 
6.0%
r148
 
4.0%
c148
 
4.0%
Other values (8)814
22.0%
Decimal Number
ValueCountFrequency (%)
889
13.3%
185
12.7%
283
12.4%
780
12.0%
365
9.7%
062
9.3%
557
8.5%
453
7.9%
648
7.2%
947
7.0%
Other Punctuation
ValueCountFrequency (%)
/518
63.6%
.222
27.3%
:74
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3700
70.4%
Common1557
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t518
14.0%
a370
10.0%
m370
10.0%
p296
 
8.0%
s296
 
8.0%
i296
 
8.0%
e222
 
6.0%
o222
 
6.0%
r148
 
4.0%
c148
 
4.0%
Other values (8)814
22.0%
Common
ValueCountFrequency (%)
/518
33.3%
.222
14.3%
889
 
5.7%
185
 
5.5%
283
 
5.3%
780
 
5.1%
_74
 
4.8%
:74
 
4.8%
365
 
4.2%
062
 
4.0%
Other values (4)205
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII5257
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t518
 
9.9%
/518
 
9.9%
a370
 
7.0%
m370
 
7.0%
p296
 
5.6%
s296
 
5.6%
i296
 
5.6%
.222
 
4.2%
e222
 
4.2%
o222
 
4.2%
Other values (22)1927
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct60
Distinct (%)81.1%
Missing7
Missing (%)8.6%
Memory size776.0 B
https://static.tvmaze.com/uploads/images/original_untouched/287/719881.jpg
 
4
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg
 
2
Other values (55)
62 

Length

Max length75
Median length74
Mean length74.04054054
Min length73

Characters and Unicode

Total characters5479
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)64.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/283/709704.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/259/648137.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/719881.jpg4
 
4.9%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/291/729458.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.5%
https://static.tvmaze.com/uploads/images/original_untouched/285/713076.jpg2
 
2.5%
Other values (50)52
64.2%
(Missing)7
 
8.6%

Length

2022-09-05T21:36:17.756679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/287/719881.jpg4
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713076.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/720951.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/350/877137.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721821.jpg2
 
2.7%
Other values (50)52
70.3%

Most occurring characters

ValueCountFrequency (%)
/518
 
9.5%
t444
 
8.1%
a370
 
6.8%
s296
 
5.4%
i296
 
5.4%
o296
 
5.4%
p222
 
4.1%
c222
 
4.1%
.222
 
4.1%
g222
 
4.1%
Other values (23)2371
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3922
71.6%
Other Punctuation814
 
14.9%
Decimal Number669
 
12.2%
Connector Punctuation74
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t444
 
11.3%
a370
 
9.4%
s296
 
7.5%
i296
 
7.5%
o296
 
7.5%
p222
 
5.7%
c222
 
5.7%
g222
 
5.7%
m222
 
5.7%
e222
 
5.7%
Other values (9)1110
28.3%
Decimal Number
ValueCountFrequency (%)
889
13.3%
185
12.7%
283
12.4%
780
12.0%
365
9.7%
062
9.3%
557
8.5%
453
7.9%
648
7.2%
947
7.0%
Other Punctuation
ValueCountFrequency (%)
/518
63.6%
.222
27.3%
:74
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3922
71.6%
Common1557
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t444
 
11.3%
a370
 
9.4%
s296
 
7.5%
i296
 
7.5%
o296
 
7.5%
p222
 
5.7%
c222
 
5.7%
g222
 
5.7%
m222
 
5.7%
e222
 
5.7%
Other values (9)1110
28.3%
Common
ValueCountFrequency (%)
/518
33.3%
.222
14.3%
889
 
5.7%
185
 
5.5%
283
 
5.3%
780
 
5.1%
:74
 
4.8%
_74
 
4.8%
365
 
4.2%
062
 
4.0%
Other values (4)205
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII5479
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/518
 
9.5%
t444
 
8.1%
a370
 
6.8%
s296
 
5.4%
i296
 
5.4%
o296
 
5.4%
p222
 
4.1%
c222
 
4.1%
.222
 
4.1%
g222
 
4.1%
Other values (23)2371
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct53
Distinct (%)81.5%
Missing16
Missing (%)19.8%
Memory size776.0 B
<p>Applying the laws of life on Earth to the rest of the galaxy, this series blends science fact and fiction to imagine alien life on other planets.</p>
 
4
<p>Morten shows you how you can make something cool with what you have at home!</p>
 
2
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>
 
2
<p>The police are investigating a case that involves a death directly caused by a rare bug known as the bullet ant. In order to clear his name, Tan Jingtian, an Insect toxicology graduate becomes involved in the bizzare investigation and collaborates with forensic doctor Jin Ling. As they dig deeper, they uncover the mystery behind his own identity.</p><p>Along with police captain Chen Han and the other detectives, they trace every clue as they solve one case at a time to uncover the murderer that has been in hiding for many years.</p>
 
2
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>
 
2
Other values (48)
53 

Length

Max length1084
Median length278
Mean length319.4615385
Min length50

Characters and Unicode

Total characters20765
Distinct characters84
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)66.2%

Sample

1st row<p><b>Mermaid Prince</b> is about Hye Ri, who embarks on a graduation trip to Gangwon Province and meets Woo Hyuk, a mysterious guy who runs a guest house.</p>
2nd row<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>
3rd row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
4th row<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>
5th row<p>Re-imagines famous firearms as moe girls with machine bodies that are known as T-Dolls.</p>

Common Values

ValueCountFrequency (%)
<p>Applying the laws of life on Earth to the rest of the galaxy, this series blends science fact and fiction to imagine alien life on other planets.</p>4
 
4.9%
<p>Morten shows you how you can make something cool with what you have at home!</p>2
 
2.5%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.5%
<p>The police are investigating a case that involves a death directly caused by a rare bug known as the bullet ant. In order to clear his name, Tan Jingtian, an Insect toxicology graduate becomes involved in the bizzare investigation and collaborates with forensic doctor Jin Ling. As they dig deeper, they uncover the mystery behind his own identity.</p><p>Along with police captain Chen Han and the other detectives, they trace every clue as they solve one case at a time to uncover the murderer that has been in hiding for many years.</p>2
 
2.5%
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>2
 
2.5%
<p>A story that follows a detective in the major crimes division of Nan Xing City Police Department. Together with a woman who has super memory, he upholds the law one case at a time in solving murders, burglaries and bringing down a narcotics manufacturing facility. Jing Chu is a young and capable detective. Due to his repeated merits from cracking big cases, he is promoted to the position of major crimes division vice-captain at Nan Xing city and starts to work alongside his new team. Because of a murder case, he meets Yang Mian Mian, a young woman who possesses a photographic memory. He soon realizes that Mian Mian seems to have a deep connection to his father's mysterious death many years ago. Meanwhile, a famous blogger and a member of an idol girl group die</p>2
 
2.5%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
2.5%
<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>2
 
2.5%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
2.5%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>2
 
2.5%
Other values (43)43
53.1%
(Missing)16
 
19.8%

Length

2022-09-05T21:36:17.877210image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the174
 
5.0%
and118
 
3.4%
to115
 
3.3%
a106
 
3.0%
of84
 
2.4%
in65
 
1.9%
his47
 
1.3%
with41
 
1.2%
on31
 
0.9%
that28
 
0.8%
Other values (1255)2693
76.9%

Most occurring characters

ValueCountFrequency (%)
3436
16.5%
e1946
 
9.4%
a1309
 
6.3%
t1276
 
6.1%
n1240
 
6.0%
i1183
 
5.7%
o1160
 
5.6%
s977
 
4.7%
r900
 
4.3%
h771
 
3.7%
Other values (74)6567
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15491
74.6%
Space Separator3438
 
16.6%
Uppercase Letter738
 
3.6%
Other Punctuation574
 
2.8%
Math Symbol416
 
2.0%
Dash Punctuation41
 
0.2%
Decimal Number37
 
0.2%
Format16
 
0.1%
Open Punctuation7
 
< 0.1%
Close Punctuation7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1946
12.6%
a1309
 
8.5%
t1276
 
8.2%
n1240
 
8.0%
i1183
 
7.6%
o1160
 
7.5%
s977
 
6.3%
r900
 
5.8%
h771
 
5.0%
l644
 
4.2%
Other values (19)4085
26.4%
Uppercase Letter
ValueCountFrequency (%)
S72
 
9.8%
T54
 
7.3%
W47
 
6.4%
H45
 
6.1%
A43
 
5.8%
M43
 
5.8%
L33
 
4.5%
E32
 
4.3%
B32
 
4.3%
D31
 
4.2%
Other values (16)306
41.5%
Other Punctuation
ValueCountFrequency (%)
,192
33.4%
.173
30.1%
/114
19.9%
'46
 
8.0%
"16
 
2.8%
!13
 
2.3%
?9
 
1.6%
:5
 
0.9%
4
 
0.7%
;1
 
0.2%
Decimal Number
ValueCountFrequency (%)
011
29.7%
18
21.6%
26
16.2%
94
 
10.8%
83
 
8.1%
32
 
5.4%
72
 
5.4%
61
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
-33
80.5%
7
 
17.1%
1
 
2.4%
Space Separator
ValueCountFrequency (%)
3436
99.9%
 2
 
0.1%
Math Symbol
ValueCountFrequency (%)
>208
50.0%
<208
50.0%
Format
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
(7
100.0%
Close Punctuation
ValueCountFrequency (%)
)7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16229
78.2%
Common4536
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1946
12.0%
a1309
 
8.1%
t1276
 
7.9%
n1240
 
7.6%
i1183
 
7.3%
o1160
 
7.1%
s977
 
6.0%
r900
 
5.5%
h771
 
4.8%
l644
 
4.0%
Other values (45)4823
29.7%
Common
ValueCountFrequency (%)
3436
75.7%
>208
 
4.6%
<208
 
4.6%
,192
 
4.2%
.173
 
3.8%
/114
 
2.5%
'46
 
1.0%
-33
 
0.7%
"16
 
0.4%
16
 
0.4%
Other values (19)94
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII20732
99.8%
Punctuation28
 
0.1%
None5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3436
16.6%
e1946
 
9.4%
a1309
 
6.3%
t1276
 
6.2%
n1240
 
6.0%
i1183
 
5.7%
o1160
 
5.6%
s977
 
4.7%
r900
 
4.3%
h771
 
3.7%
Other values (66)6534
31.5%
Punctuation
ValueCountFrequency (%)
16
57.1%
7
25.0%
4
 
14.3%
1
 
3.6%
None
ValueCountFrequency (%)
 2
40.0%
æ1
20.0%
å1
20.0%
é1
20.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct67
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639510363
Minimum1607104092
Maximum1662346277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:17.988841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1607104092
5-th percentile1609060726
Q11619633499
median1645039616
Q31654445312
95-th percentile1662050133
Maximum1662346277
Range55242185
Interquartile range (IQR)34811813

Descriptive statistics

Standard deviation18885420.07
Coefficient of variation (CV)0.01151893913
Kurtosis-1.173834852
Mean1639510363
Median Absolute Deviation (MAD)12450400
Skewness-0.5387319133
Sum1.328003394 × 1011
Variance3.566590912 × 1014
MonotonicityNot monotonic
2022-09-05T21:36:18.099877image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16483288104
 
4.9%
16095351412
 
2.5%
16508264802
 
2.5%
16196334992
 
2.5%
16090607262
 
2.5%
16549774442
 
2.5%
16096068542
 
2.5%
16076979652
 
2.5%
16574900162
 
2.5%
16357351792
 
2.5%
Other values (57)59
72.8%
ValueCountFrequency (%)
16071040921
1.2%
16076979652
2.5%
16090607262
2.5%
16095351412
2.5%
16096068542
2.5%
16102051551
1.2%
16108125261
1.2%
16108903401
1.2%
16114368421
1.2%
16120078311
1.2%
ValueCountFrequency (%)
16623462771
1.2%
16622756681
1.2%
16622629611
1.2%
16622179311
1.2%
16620501331
1.2%
16619691591
1.2%
16618725611
1.2%
16614857291
1.2%
16613636671
1.2%
16613636441
1.2%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size776.0 B
https://api.tvmaze.com/shows/51927
 
4
https://api.tvmaze.com/shows/52104
 
2
https://api.tvmaze.com/shows/52108
 
2
https://api.tvmaze.com/shows/52421
 
2
https://api.tvmaze.com/shows/52159
 
2
Other values (62)
69 

Length

Max length34
Median length34
Mean length33.97530864
Min length33

Characters and Unicode

Total characters2752
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)67.9%

Sample

1st rowhttps://api.tvmaze.com/shows/49630
2nd rowhttps://api.tvmaze.com/shows/52198
3rd rowhttps://api.tvmaze.com/shows/47207
4th rowhttps://api.tvmaze.com/shows/48395
5th rowhttps://api.tvmaze.com/shows/49206

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/519274
 
4.9%
https://api.tvmaze.com/shows/521042
 
2.5%
https://api.tvmaze.com/shows/521082
 
2.5%
https://api.tvmaze.com/shows/524212
 
2.5%
https://api.tvmaze.com/shows/521592
 
2.5%
https://api.tvmaze.com/shows/527802
 
2.5%
https://api.tvmaze.com/shows/518702
 
2.5%
https://api.tvmaze.com/shows/520382
 
2.5%
https://api.tvmaze.com/shows/570302
 
2.5%
https://api.tvmaze.com/shows/586892
 
2.5%
Other values (57)59
72.8%

Length

2022-09-05T21:36:18.194546image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/519274
 
4.9%
https://api.tvmaze.com/shows/518702
 
2.5%
https://api.tvmaze.com/shows/521072
 
2.5%
https://api.tvmaze.com/shows/521062
 
2.5%
https://api.tvmaze.com/shows/586892
 
2.5%
https://api.tvmaze.com/shows/520382
 
2.5%
https://api.tvmaze.com/shows/570302
 
2.5%
https://api.tvmaze.com/shows/527802
 
2.5%
https://api.tvmaze.com/shows/521592
 
2.5%
https://api.tvmaze.com/shows/524212
 
2.5%
Other values (57)59
72.8%

Most occurring characters

ValueCountFrequency (%)
/324
 
11.8%
s243
 
8.8%
t243
 
8.8%
h162
 
5.9%
p162
 
5.9%
a162
 
5.9%
o162
 
5.9%
.162
 
5.9%
m162
 
5.9%
e81
 
2.9%
Other values (16)889
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1782
64.8%
Other Punctuation567
 
20.6%
Decimal Number403
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s243
13.6%
t243
13.6%
h162
9.1%
p162
9.1%
a162
9.1%
o162
9.1%
m162
9.1%
e81
 
4.5%
w81
 
4.5%
c81
 
4.5%
Other values (3)243
13.6%
Decimal Number
ValueCountFrequency (%)
573
18.1%
449
12.2%
144
10.9%
242
10.4%
735
8.7%
035
8.7%
635
8.7%
933
8.2%
331
7.7%
826
 
6.5%
Other Punctuation
ValueCountFrequency (%)
/324
57.1%
.162
28.6%
:81
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1782
64.8%
Common970
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/324
33.4%
.162
16.7%
:81
 
8.4%
573
 
7.5%
449
 
5.1%
144
 
4.5%
242
 
4.3%
735
 
3.6%
035
 
3.6%
635
 
3.6%
Other values (3)90
 
9.3%
Latin
ValueCountFrequency (%)
s243
13.6%
t243
13.6%
h162
9.1%
p162
9.1%
a162
9.1%
o162
9.1%
m162
9.1%
e81
 
4.5%
w81
 
4.5%
c81
 
4.5%
Other values (3)243
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2752
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/324
 
11.8%
s243
 
8.8%
t243
 
8.8%
h162
 
5.9%
p162
 
5.9%
a162
 
5.9%
o162
 
5.9%
.162
 
5.9%
m162
 
5.9%
e81
 
2.9%
Other values (16)889
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct67
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size776.0 B
https://api.tvmaze.com/episodes/1978291
 
4
https://api.tvmaze.com/episodes/1976054
 
2
https://api.tvmaze.com/episodes/1976202
 
2
https://api.tvmaze.com/episodes/1985496
 
2
https://api.tvmaze.com/episodes/1977651
 
2
Other values (62)
69 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3159
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)67.9%

Sample

1st rowhttps://api.tvmaze.com/episodes/2380515
2nd rowhttps://api.tvmaze.com/episodes/1986873
3rd rowhttps://api.tvmaze.com/episodes/1971570
4th rowhttps://api.tvmaze.com/episodes/2280228
5th rowhttps://api.tvmaze.com/episodes/2386129

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19782914
 
4.9%
https://api.tvmaze.com/episodes/19760542
 
2.5%
https://api.tvmaze.com/episodes/19762022
 
2.5%
https://api.tvmaze.com/episodes/19854962
 
2.5%
https://api.tvmaze.com/episodes/19776512
 
2.5%
https://api.tvmaze.com/episodes/19985382
 
2.5%
https://api.tvmaze.com/episodes/19685502
 
2.5%
https://api.tvmaze.com/episodes/19735452
 
2.5%
https://api.tvmaze.com/episodes/21701272
 
2.5%
https://api.tvmaze.com/episodes/22059832
 
2.5%
Other values (57)59
72.8%

Length

2022-09-05T21:36:18.277201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19782914
 
4.9%
https://api.tvmaze.com/episodes/19685502
 
2.5%
https://api.tvmaze.com/episodes/19761662
 
2.5%
https://api.tvmaze.com/episodes/19761372
 
2.5%
https://api.tvmaze.com/episodes/22059832
 
2.5%
https://api.tvmaze.com/episodes/19735452
 
2.5%
https://api.tvmaze.com/episodes/21701272
 
2.5%
https://api.tvmaze.com/episodes/19985382
 
2.5%
https://api.tvmaze.com/episodes/19776512
 
2.5%
https://api.tvmaze.com/episodes/19854962
 
2.5%
Other values (57)59
72.8%

Most occurring characters

ValueCountFrequency (%)
/324
 
10.3%
t243
 
7.7%
p243
 
7.7%
s243
 
7.7%
e243
 
7.7%
a162
 
5.1%
i162
 
5.1%
.162
 
5.1%
m162
 
5.1%
o162
 
5.1%
Other values (16)1053
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2025
64.1%
Other Punctuation567
 
17.9%
Decimal Number567
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t243
12.0%
p243
12.0%
s243
12.0%
e243
12.0%
a162
8.0%
i162
8.0%
m162
8.0%
o162
8.0%
h81
 
4.0%
d81
 
4.0%
Other values (3)243
12.0%
Decimal Number
ValueCountFrequency (%)
2101
17.8%
172
12.7%
970
12.3%
764
11.3%
351
9.0%
548
8.5%
047
8.3%
643
7.6%
841
7.2%
430
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/324
57.1%
.162
28.6%
:81
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2025
64.1%
Common1134
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/324
28.6%
.162
14.3%
2101
 
8.9%
:81
 
7.1%
172
 
6.3%
970
 
6.2%
764
 
5.6%
351
 
4.5%
548
 
4.2%
047
 
4.1%
Other values (3)114
 
10.1%
Latin
ValueCountFrequency (%)
t243
12.0%
p243
12.0%
s243
12.0%
e243
12.0%
a162
8.0%
i162
8.0%
m162
8.0%
o162
8.0%
h81
 
4.0%
d81
 
4.0%
Other values (3)243
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3159
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/324
 
10.3%
t243
 
7.7%
p243
 
7.7%
s243
 
7.7%
e243
 
7.7%
a162
 
5.1%
i162
 
5.1%
.162
 
5.1%
m162
 
5.1%
o162
 
5.1%
Other values (16)1053
33.3%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)23.3%
Missing38
Missing (%)46.9%
Memory size776.0 B
China
22 
Norway
United States
Korea, Republic of
Russian Federation
 
2
Other values (5)

Length

Max length18
Median length5
Mean length7.930232558
Min length5

Characters and Unicode

Total characters341
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)11.6%

Sample

1st rowRussian Federation
2nd rowKorea, Republic of
3rd rowChina
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China22
27.2%
Norway6
 
7.4%
United States5
 
6.2%
Korea, Republic of3
 
3.7%
Russian Federation2
 
2.5%
United Kingdom1
 
1.2%
Kazakhstan1
 
1.2%
Japan1
 
1.2%
Egypt1
 
1.2%
Brazil1
 
1.2%
(Missing)38
46.9%

Length

2022-09-05T21:36:18.365445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:18.472436image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china22
38.6%
norway6
 
10.5%
united6
 
10.5%
states5
 
8.8%
korea3
 
5.3%
republic3
 
5.3%
of3
 
5.3%
russian2
 
3.5%
federation2
 
3.5%
kingdom1
 
1.8%
Other values (4)4
 
7.0%

Most occurring characters

ValueCountFrequency (%)
a46
13.5%
i37
 
10.9%
n35
 
10.3%
h23
 
6.7%
C22
 
6.5%
e21
 
6.2%
t20
 
5.9%
o15
 
4.4%
14
 
4.1%
r12
 
3.5%
Other values (24)96
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter270
79.2%
Uppercase Letter54
 
15.8%
Space Separator14
 
4.1%
Other Punctuation3
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a46
17.0%
i37
13.7%
n35
13.0%
h23
8.5%
e21
7.8%
t20
7.4%
o15
 
5.6%
r12
 
4.4%
s10
 
3.7%
d9
 
3.3%
Other values (12)42
15.6%
Uppercase Letter
ValueCountFrequency (%)
C22
40.7%
U6
 
11.1%
N6
 
11.1%
R5
 
9.3%
K5
 
9.3%
S5
 
9.3%
F2
 
3.7%
J1
 
1.9%
E1
 
1.9%
B1
 
1.9%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin324
95.0%
Common17
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a46
14.2%
i37
11.4%
n35
10.8%
h23
 
7.1%
C22
 
6.8%
e21
 
6.5%
t20
 
6.2%
o15
 
4.6%
r12
 
3.7%
s10
 
3.1%
Other values (22)83
25.6%
Common
ValueCountFrequency (%)
14
82.4%
,3
 
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII341
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a46
13.5%
i37
 
10.9%
n35
 
10.3%
h23
 
6.7%
C22
 
6.5%
e21
 
6.2%
t20
 
5.9%
o15
 
4.4%
14
 
4.1%
r12
 
3.5%
Other values (24)96
28.2%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)23.3%
Missing38
Missing (%)46.9%
Memory size776.0 B
CN
22 
NO
US
KR
RU
 
2
Other values (5)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters86
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)11.6%

Sample

1st rowRU
2nd rowKR
3rd rowCN
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN22
27.2%
NO6
 
7.4%
US5
 
6.2%
KR3
 
3.7%
RU2
 
2.5%
GB1
 
1.2%
KZ1
 
1.2%
JP1
 
1.2%
EG1
 
1.2%
BR1
 
1.2%
(Missing)38
46.9%

Length

2022-09-05T21:36:18.557046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:18.658377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn22
51.2%
no6
 
14.0%
us5
 
11.6%
kr3
 
7.0%
ru2
 
4.7%
gb1
 
2.3%
kz1
 
2.3%
jp1
 
2.3%
eg1
 
2.3%
br1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
N28
32.6%
C22
25.6%
U7
 
8.1%
O6
 
7.0%
R6
 
7.0%
S5
 
5.8%
K4
 
4.7%
G2
 
2.3%
B2
 
2.3%
Z1
 
1.2%
Other values (3)3
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter86
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N28
32.6%
C22
25.6%
U7
 
8.1%
O6
 
7.0%
R6
 
7.0%
S5
 
5.8%
K4
 
4.7%
G2
 
2.3%
B2
 
2.3%
Z1
 
1.2%
Other values (3)3
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Latin86
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N28
32.6%
C22
25.6%
U7
 
8.1%
O6
 
7.0%
R6
 
7.0%
S5
 
5.8%
K4
 
4.7%
G2
 
2.3%
B2
 
2.3%
Z1
 
1.2%
Other values (3)3
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII86
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N28
32.6%
C22
25.6%
U7
 
8.1%
O6
 
7.0%
R6
 
7.0%
S5
 
5.8%
K4
 
4.7%
G2
 
2.3%
B2
 
2.3%
Z1
 
1.2%
Other values (3)3
 
3.5%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)23.3%
Missing38
Missing (%)46.9%
Memory size776.0 B
Asia/Shanghai
22 
Europe/Oslo
America/New_York
Asia/Seoul
Asia/Kamchatka
 
2
Other values (5)

Length

Max length16
Median length13
Mean length12.88372093
Min length10

Characters and Unicode

Total characters554
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)11.6%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Seoul
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai22
27.2%
Europe/Oslo6
 
7.4%
America/New_York5
 
6.2%
Asia/Seoul3
 
3.7%
Asia/Kamchatka2
 
2.5%
Europe/London1
 
1.2%
Asia/Qyzylorda1
 
1.2%
Asia/Tokyo1
 
1.2%
Africa/Cairo1
 
1.2%
America/Noronha1
 
1.2%
(Missing)38
46.9%

Length

2022-09-05T21:36:18.748336image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:18.855994image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai22
51.2%
europe/oslo6
 
14.0%
america/new_york5
 
11.6%
asia/seoul3
 
7.0%
asia/kamchatka2
 
4.7%
europe/london1
 
2.3%
asia/qyzylorda1
 
2.3%
asia/tokyo1
 
2.3%
africa/cairo1
 
2.3%
america/noronha1
 
2.3%

Most occurring characters

ValueCountFrequency (%)
a89
16.1%
i59
10.6%
h47
 
8.5%
/43
 
7.8%
A36
 
6.5%
s35
 
6.3%
o29
 
5.2%
S25
 
4.5%
n25
 
4.5%
g22
 
4.0%
Other values (24)144
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter415
74.9%
Uppercase Letter91
 
16.4%
Other Punctuation43
 
7.8%
Connector Punctuation5
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a89
21.4%
i59
14.2%
h47
11.3%
s35
 
8.4%
o29
 
7.0%
n25
 
6.0%
g22
 
5.3%
r22
 
5.3%
e21
 
5.1%
l10
 
2.4%
Other values (11)56
13.5%
Uppercase Letter
ValueCountFrequency (%)
A36
39.6%
S25
27.5%
E7
 
7.7%
O6
 
6.6%
N6
 
6.6%
Y5
 
5.5%
K2
 
2.2%
L1
 
1.1%
Q1
 
1.1%
T1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/43
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin506
91.3%
Common48
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a89
17.6%
i59
11.7%
h47
9.3%
A36
 
7.1%
s35
 
6.9%
o29
 
5.7%
S25
 
4.9%
n25
 
4.9%
g22
 
4.3%
r22
 
4.3%
Other values (22)117
23.1%
Common
ValueCountFrequency (%)
/43
89.6%
_5
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a89
16.1%
i59
10.6%
h47
 
8.5%
/43
 
7.8%
A36
 
6.5%
s35
 
6.3%
o29
 
5.2%
S25
 
4.5%
n25
 
4.5%
g22
 
4.0%
Other values (24)144
26.0%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing75
Missing (%)92.6%
Memory size776.0 B
https://api.tvmaze.com/episodes/2374449
https://api.tvmaze.com/episodes/2373586
https://api.tvmaze.com/episodes/2376729
https://api.tvmaze.com/episodes/2371586
https://api.tvmaze.com/episodes/2379703

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters234
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2374449
2nd rowhttps://api.tvmaze.com/episodes/2373586
3rd rowhttps://api.tvmaze.com/episodes/2376729
4th rowhttps://api.tvmaze.com/episodes/2371586
5th rowhttps://api.tvmaze.com/episodes/2379703

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
 
1.2%
https://api.tvmaze.com/episodes/23735861
 
1.2%
https://api.tvmaze.com/episodes/23767291
 
1.2%
https://api.tvmaze.com/episodes/23715861
 
1.2%
https://api.tvmaze.com/episodes/23797031
 
1.2%
https://api.tvmaze.com/episodes/23671071
 
1.2%
(Missing)75
92.6%

Length

2022-09-05T21:36:18.945242image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:19.036680image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
16.7%
https://api.tvmaze.com/episodes/23735861
16.7%
https://api.tvmaze.com/episodes/23767291
16.7%
https://api.tvmaze.com/episodes/23715861
16.7%
https://api.tvmaze.com/episodes/23797031
16.7%
https://api.tvmaze.com/episodes/23671071
16.7%

Most occurring characters

ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter150
64.1%
Other Punctuation42
 
17.9%
Decimal Number42
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%
Decimal Number
ValueCountFrequency (%)
79
21.4%
38
19.0%
27
16.7%
64
9.5%
43
 
7.1%
93
 
7.1%
52
 
4.8%
82
 
4.8%
12
 
4.8%
02
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/24
57.1%
.12
28.6%
:6
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin150
64.1%
Common84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/24
28.6%
.12
14.3%
79
 
10.7%
38
 
9.5%
27
 
8.3%
:6
 
7.1%
64
 
4.8%
43
 
3.6%
93
 
3.6%
52
 
2.4%
Other values (3)6
 
7.1%
Latin
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)100.0%
Missing73
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean638.625
Minimum30
Maximum1862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size776.0 B
2022-09-05T21:36:19.111390image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile58.7
Q1127
median388
Q3806.25
95-th percentile1799.35
Maximum1862
Range1832
Interquartile range (IQR)679.25

Descriptive statistics

Standard deviation720.4504419
Coefficient of variation (CV)1.128127527
Kurtosis-0.1685403428
Mean638.625
Median Absolute Deviation (MAD)266
Skewness1.240214512
Sum5109
Variance519048.8393
MonotonicityNot monotonic
2022-09-05T21:36:19.186501image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
5141
 
1.2%
18621
 
1.2%
16831
 
1.2%
3741
 
1.2%
4021
 
1.2%
1121
 
1.2%
301
 
1.2%
1321
 
1.2%
(Missing)73
90.1%
ValueCountFrequency (%)
301
1.2%
1121
1.2%
1321
1.2%
3741
1.2%
4021
1.2%
5141
1.2%
16831
1.2%
18621
1.2%
ValueCountFrequency (%)
18621
1.2%
16831
1.2%
5141
1.2%
4021
1.2%
3741
1.2%
1321
1.2%
1121
1.2%
301
1.2%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct8
Distinct (%)100.0%
Missing73
Missing (%)90.1%
Memory size776.0 B
ТВ-3
AfricaMagic Showcase
DMC
TV Globo
Новий Канал
Other values (3)

Length

Max length20
Median length9.5
Mean length8.625
Min length3

Characters and Unicode

Total characters69
Distinct characters44
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowТВ-3
2nd rowAfricaMagic Showcase
3rd rowDMC
4th rowTV Globo
5th rowНовий Канал

Common Values

ValueCountFrequency (%)
ТВ-31
 
1.2%
AfricaMagic Showcase1
 
1.2%
DMC1
 
1.2%
TV Globo1
 
1.2%
Новий Канал1
 
1.2%
RTL41
 
1.2%
USA Network1
 
1.2%
Tokyo MX1
 
1.2%
(Missing)73
90.1%

Length

2022-09-05T21:36:19.274804image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:19.384407image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
тв-31
 
7.7%
africamagic1
 
7.7%
showcase1
 
7.7%
dmc1
 
7.7%
tv1
 
7.7%
globo1
 
7.7%
новий1
 
7.7%
канал1
 
7.7%
rtl41
 
7.7%
usa1
 
7.7%
Other values (3)3
23.1%

Most occurring characters

ValueCountFrequency (%)
o6
 
8.7%
5
 
7.2%
M3
 
4.3%
c3
 
4.3%
a3
 
4.3%
T3
 
4.3%
r2
 
2.9%
i2
 
2.9%
A2
 
2.9%
а2
 
2.9%
Other values (34)38
55.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38
55.1%
Uppercase Letter23
33.3%
Space Separator5
 
7.2%
Decimal Number2
 
2.9%
Dash Punctuation1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o6
15.8%
c3
 
7.9%
a3
 
7.9%
r2
 
5.3%
i2
 
5.3%
а2
 
5.3%
k2
 
5.3%
w2
 
5.3%
e2
 
5.3%
н1
 
2.6%
Other values (13)13
34.2%
Uppercase Letter
ValueCountFrequency (%)
M3
13.0%
T3
13.0%
A2
 
8.7%
S2
 
8.7%
К1
 
4.3%
R1
 
4.3%
Т1
 
4.3%
U1
 
4.3%
L1
 
4.3%
N1
 
4.3%
Other values (7)7
30.4%
Decimal Number
ValueCountFrequency (%)
41
50.0%
31
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin49
71.0%
Cyrillic12
 
17.4%
Common8
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o6
 
12.2%
M3
 
6.1%
c3
 
6.1%
a3
 
6.1%
T3
 
6.1%
r2
 
4.1%
i2
 
4.1%
A2
 
4.1%
k2
 
4.1%
S2
 
4.1%
Other values (19)21
42.9%
Cyrillic
ValueCountFrequency (%)
а2
16.7%
К1
8.3%
н1
8.3%
й1
8.3%
л1
8.3%
Т1
8.3%
в1
8.3%
и1
8.3%
о1
8.3%
Н1
8.3%
Common
ValueCountFrequency (%)
5
62.5%
41
 
12.5%
31
 
12.5%
-1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII57
82.6%
Cyrillic12
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o6
 
10.5%
5
 
8.8%
M3
 
5.3%
c3
 
5.3%
a3
 
5.3%
T3
 
5.3%
r2
 
3.5%
i2
 
3.5%
A2
 
3.5%
k2
 
3.5%
Other values (23)26
45.6%
Cyrillic
ValueCountFrequency (%)
а2
16.7%
К1
8.3%
н1
8.3%
й1
8.3%
л1
8.3%
Т1
8.3%
в1
8.3%
и1
8.3%
о1
8.3%
Н1
8.3%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct8
Distinct (%)100.0%
Missing73
Missing (%)90.1%
Memory size776.0 B
Russian Federation
South Africa
Egypt
Brazil
Ukraine
Other values (3)

Length

Max length18
Median length11.5
Mean length9.625
Min length5

Characters and Unicode

Total characters77
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowRussian Federation
2nd rowSouth Africa
3rd rowEgypt
4th rowBrazil
5th rowUkraine

Common Values

ValueCountFrequency (%)
Russian Federation1
 
1.2%
South Africa1
 
1.2%
Egypt1
 
1.2%
Brazil1
 
1.2%
Ukraine1
 
1.2%
Netherlands1
 
1.2%
United States1
 
1.2%
Japan1
 
1.2%
(Missing)73
90.1%

Length

2022-09-05T21:36:19.480395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:19.583648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
russian1
9.1%
federation1
9.1%
south1
9.1%
africa1
9.1%
egypt1
9.1%
brazil1
9.1%
ukraine1
9.1%
netherlands1
9.1%
united1
9.1%
states1
9.1%

Most occurring characters

ValueCountFrequency (%)
a9
 
11.7%
e7
 
9.1%
t7
 
9.1%
i6
 
7.8%
n6
 
7.8%
r5
 
6.5%
s4
 
5.2%
3
 
3.9%
d3
 
3.9%
S2
 
2.6%
Other values (19)25
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter63
81.8%
Uppercase Letter11
 
14.3%
Space Separator3
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a9
14.3%
e7
11.1%
t7
11.1%
i6
9.5%
n6
9.5%
r5
7.9%
s4
 
6.3%
d3
 
4.8%
l2
 
3.2%
u2
 
3.2%
Other values (9)12
19.0%
Uppercase Letter
ValueCountFrequency (%)
S2
18.2%
U2
18.2%
N1
9.1%
B1
9.1%
R1
9.1%
E1
9.1%
A1
9.1%
F1
9.1%
J1
9.1%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin74
96.1%
Common3
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a9
 
12.2%
e7
 
9.5%
t7
 
9.5%
i6
 
8.1%
n6
 
8.1%
r5
 
6.8%
s4
 
5.4%
d3
 
4.1%
S2
 
2.7%
l2
 
2.7%
Other values (18)23
31.1%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII77
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a9
 
11.7%
e7
 
9.1%
t7
 
9.1%
i6
 
7.8%
n6
 
7.8%
r5
 
6.5%
s4
 
5.2%
3
 
3.9%
d3
 
3.9%
S2
 
2.6%
Other values (19)25
32.5%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct8
Distinct (%)100.0%
Missing73
Missing (%)90.1%
Memory size776.0 B
RU
ZA
EG
BR
UA
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters16
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowRU
2nd rowZA
3rd rowEG
4th rowBR
5th rowUA

Common Values

ValueCountFrequency (%)
RU1
 
1.2%
ZA1
 
1.2%
EG1
 
1.2%
BR1
 
1.2%
UA1
 
1.2%
NL1
 
1.2%
US1
 
1.2%
JP1
 
1.2%
(Missing)73
90.1%

Length

2022-09-05T21:36:19.672778image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:19.773260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ru1
12.5%
za1
12.5%
eg1
12.5%
br1
12.5%
ua1
12.5%
nl1
12.5%
us1
12.5%
jp1
12.5%

Most occurring characters

ValueCountFrequency (%)
U3
18.8%
R2
12.5%
A2
12.5%
Z1
 
6.2%
E1
 
6.2%
G1
 
6.2%
B1
 
6.2%
N1
 
6.2%
L1
 
6.2%
S1
 
6.2%
Other values (2)2
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter16
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U3
18.8%
R2
12.5%
A2
12.5%
Z1
 
6.2%
E1
 
6.2%
G1
 
6.2%
B1
 
6.2%
N1
 
6.2%
L1
 
6.2%
S1
 
6.2%
Other values (2)2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U3
18.8%
R2
12.5%
A2
12.5%
Z1
 
6.2%
E1
 
6.2%
G1
 
6.2%
B1
 
6.2%
N1
 
6.2%
L1
 
6.2%
S1
 
6.2%
Other values (2)2
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U3
18.8%
R2
12.5%
A2
12.5%
Z1
 
6.2%
E1
 
6.2%
G1
 
6.2%
B1
 
6.2%
N1
 
6.2%
L1
 
6.2%
S1
 
6.2%
Other values (2)2
12.5%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct8
Distinct (%)100.0%
Missing73
Missing (%)90.1%
Memory size776.0 B
Asia/Kamchatka
Africa/Johannesburg
Africa/Cairo
America/Noronha
Europe/Zaporozhye
Other values (3)

Length

Max length19
Median length15.5
Mean length14.875
Min length10

Characters and Unicode

Total characters119
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st rowAsia/Kamchatka
2nd rowAfrica/Johannesburg
3rd rowAfrica/Cairo
4th rowAmerica/Noronha
5th rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Asia/Kamchatka1
 
1.2%
Africa/Johannesburg1
 
1.2%
Africa/Cairo1
 
1.2%
America/Noronha1
 
1.2%
Europe/Zaporozhye1
 
1.2%
Europe/Amsterdam1
 
1.2%
America/New_York1
 
1.2%
Asia/Tokyo1
 
1.2%
(Missing)73
90.1%

Length

2022-09-05T21:36:19.869192image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:19.972970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/kamchatka1
12.5%
africa/johannesburg1
12.5%
africa/cairo1
12.5%
america/noronha1
12.5%
europe/zaporozhye1
12.5%
europe/amsterdam1
12.5%
america/new_york1
12.5%
asia/tokyo1
12.5%

Most occurring characters

ValueCountFrequency (%)
a14
 
11.8%
r12
 
10.1%
o11
 
9.2%
e8
 
6.7%
/8
 
6.7%
A7
 
5.9%
i7
 
5.9%
m5
 
4.2%
c5
 
4.2%
h4
 
3.4%
Other values (22)38
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter93
78.2%
Uppercase Letter17
 
14.3%
Other Punctuation8
 
6.7%
Connector Punctuation1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a14
15.1%
r12
12.9%
o11
11.8%
e8
 
8.6%
i7
 
7.5%
m5
 
5.4%
c5
 
5.4%
h4
 
4.3%
s4
 
4.3%
p3
 
3.2%
Other values (11)20
21.5%
Uppercase Letter
ValueCountFrequency (%)
A7
41.2%
N2
 
11.8%
E2
 
11.8%
Y1
 
5.9%
Z1
 
5.9%
C1
 
5.9%
J1
 
5.9%
K1
 
5.9%
T1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin110
92.4%
Common9
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a14
12.7%
r12
 
10.9%
o11
 
10.0%
e8
 
7.3%
A7
 
6.4%
i7
 
6.4%
m5
 
4.5%
c5
 
4.5%
h4
 
3.6%
s4
 
3.6%
Other values (20)33
30.0%
Common
ValueCountFrequency (%)
/8
88.9%
_1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a14
 
11.8%
r12
 
10.1%
o11
 
9.2%
e8
 
6.7%
/8
 
6.7%
A7
 
5.9%
i7
 
5.9%
m5
 
4.2%
c5
 
4.2%
h4
 
3.4%
Other values (22)38
31.9%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing81
Missing (%)100.0%
Memory size776.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing80
Missing (%)98.8%
Memory size776.0 B
Ukraine

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUkraine

Common Values

ValueCountFrequency (%)
Ukraine1
 
1.2%
(Missing)80
98.8%

Length

2022-09-05T21:36:20.062420image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:20.134891image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ukraine1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6
85.7%
Uppercase Letter1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k1
16.7%
r1
16.7%
a1
16.7%
i1
16.7%
n1
16.7%
e1
16.7%
Uppercase Letter
ValueCountFrequency (%)
U1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
14.3%
k1
14.3%
r1
14.3%
a1
14.3%
i1
14.3%
n1
14.3%
e1
14.3%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing80
Missing (%)98.8%
Memory size776.0 B
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowUA

Common Values

ValueCountFrequency (%)
UA1
 
1.2%
(Missing)80
98.8%

Length

2022-09-05T21:36:20.203117image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:20.276163image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ua1
100.0%

Most occurring characters

ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U1
50.0%
A1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing80
Missing (%)98.8%
Memory size776.0 B
Europe/Zaporozhye

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Europe/Zaporozhye1
 
1.2%
(Missing)80
98.8%

Length

2022-09-05T21:36:20.343088image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:36:20.419535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
europe/zaporozhye1
100.0%

Most occurring characters

ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14
82.4%
Uppercase Letter2
 
11.8%
Other Punctuation1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
21.4%
r2
14.3%
p2
14.3%
e2
14.3%
u1
 
7.1%
a1
 
7.1%
z1
 
7.1%
h1
 
7.1%
y1
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
E1
50.0%
Z1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16
94.1%
Common1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
18.8%
r2
12.5%
p2
12.5%
e2
12.5%
E1
 
6.2%
u1
 
6.2%
Z1
 
6.2%
a1
 
6.2%
z1
 
6.2%
h1
 
6.2%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3
17.6%
r2
11.8%
p2
11.8%
e2
11.8%
E1
 
5.9%
u1
 
5.9%
/1
 
5.9%
Z1
 
5.9%
a1
 
5.9%
z1
 
5.9%
Other values (2)2
11.8%

Interactions

2022-09-05T21:36:09.875300image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:00.585816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.448267image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.259072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.048741image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.837043image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:04.634263image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.920412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.726950image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.488765image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.272835image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.075329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.941758image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:00.754865image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.514392image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.323689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.110569image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.899009image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.173417image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.988312image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.786660image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.554989image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.341467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.137956image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:10.007257image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:00.828054image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.585389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.392524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.178371image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.968365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.255813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.057816image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.856725image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.622251image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.411129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.206791image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:03.312983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:04.102947image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:01.010980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.787047image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.590529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.377791image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:04.167805image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.454945image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.258531image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.049193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.822191image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.611636image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.412115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:10.271554image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.076233image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:01.856580image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.653940image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.442571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:04.232955image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.520720image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.326114image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.112790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.887984image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.676919image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.477980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:10.340789image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:01.922049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:04.303369image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.586526image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.391421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.175370image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.952500image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.742383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:09.542977image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:10.403785image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:02.783736image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:03.573686image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:04.368304image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:05.647733image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:06.455586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:07.234479image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:08.016509image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:01.386146image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:36:02.189212image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:36:09.803508image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:36:20.506898image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:36:20.751820image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:36:20.980482image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:36:21.255421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:36:10.948003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:36:11.652801image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:36:12.620314image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01972782https://www.tvmaze.com/episodes/1972782/kontakty-1x28-kontakty-v-telefone-sergea-lazareva-timati-polina-gagarina-vlad-topalov-ida-galicКОНТАКТЫ в телефоне Сергея Лазарева: Тимати, Полина Гагарина, Влад Топалов, Ида Галич128.0regular2020-12-0212:002020-12-02T00:00:00+00:0038.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901421.jpghttps://static.tvmaze.com/uploads/images/original_untouched/360/901421.jpghttps://api.tvmaze.com/episodes/197278249630https://www.tvmaze.com/shows/49630/kontaktyКонтактыGame ShowRussian[]Running30.042.02019-04-03Nonehttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI[Monday]NaN22NaN21.0YouTubeNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpgNone1661485729https://api.tvmaze.com/shows/49630https://api.tvmaze.com/episodes/2380515NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11979223https://www.tvmaze.com/episodes/1979223/kotiki-1x03-seria-3Серия 313.0regular2020-12-022020-12-02T00:00:00+00:0013.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197922352198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN15NaN510.0Epic MediaNaNNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21971567https://www.tvmaze.com/episodes/1971567/mermaid-prince-2x07-episode-7Episode 727.0regular2020-12-0211:002020-12-02T02:00:00+00:0015.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197156747207https://www.tvmaze.com/shows/47207/mermaid-princeMermaid PrinceScriptedKorean[Drama, Romance, Mystery]Ended15.015.02020-04-142020-12-10None11:00[Wednesday, Thursday]NaN34NaN380.0SeeznNaNhttps://www.seezntv.com/NaNNaN380686.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/283/709704.jpghttps://static.tvmaze.com/uploads/images/original_untouched/283/709704.jpg<p><b>Mermaid Prince</b> is about Hye Ri, who embarks on a graduation trip to Gangwon Province and meets Woo Hyuk, a mysterious guy who runs a guest house.</p>1610205155https://api.tvmaze.com/shows/47207https://api.tvmaze.com/episodes/1971570NaNKorea, Republic ofKRAsia/SeoulNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31983072https://www.tvmaze.com/episodes/1983072/wan-sheng-jie-2x10-all-products-funds-were-spent-on-this-episodeAll products funds were spent on this episode210.0regular2020-12-0210:002020-12-02T02:00:00+00:004.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198307248395https://www.tvmaze.com/shows/48395/wan-sheng-jieWan Sheng JieAnimationChinese[Comedy, Anime, Supernatural]Running4.04.02020-04-01Nonehttps://v.qq.com/detail/a/awnia0n2erqryf3.html10:00[Wednesday]NaN16NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN380207.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/259/648137.jpghttps://static.tvmaze.com/uploads/images/original_untouched/259/648137.jpg<p>The pure and cute little devil Nini lives in Room 1031 of Wan Sheng Street Apartment. His roommates are no ordinary people: The lazy and wacky vampire Ira who spends most of his time gaming or watching TV, the unlucky dancer werewolf Vladimir, the serious and old-fashioned angel landlord Lynn and his naive little sister Lily, and many more.<br /><br />What none of them realize is that the power of the demon king is sleeping inside of Nini. With evil forces in hot pursuit, can Nini and his friends head off disaster?</p>1647193542https://api.tvmaze.com/shows/48395https://api.tvmaze.com/episodes/2280228NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
42386103https://www.tvmaze.com/episodes/2386103/xian-feng-jian-yu-lu-1x44-episode-44Episode 44144.0regular2020-12-0210:002020-12-02T02:00:00+00:008.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/238610349206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN62NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51985615https://www.tvmaze.com/episodes/1985615/yi-nian-yong-heng-1x19-episode-19Episode 19119.0regular2020-12-0210:002020-12-02T02:00:00+00:0019.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/198561549652https://www.tvmaze.com/shows/49652/yi-nian-yong-hengYi Nian Yong HengAnimationChinese[Comedy, Action, Anime, Fantasy]Running19.019.02020-08-12Nonehttps://v.qq.com/detail/w/ww18u675tfmhas6.html10:00[Wednesday]NaN56NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN388680.0tt13695606https://static.tvmaze.com/uploads/images/medium_portrait/267/669816.jpghttps://static.tvmaze.com/uploads/images/original_untouched/267/669816.jpg<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>1660662594https://api.tvmaze.com/shows/49652https://api.tvmaze.com/episodes/2374448NaNChinaCNAsia/Shanghaihttps://api.tvmaze.com/episodes/2374449NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
62030018https://www.tvmaze.com/episodes/2030018/dolls-frontline-2x10-episode-10Episode 10210.0regular2020-12-0212:002020-12-02T04:00:00+00:005.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/203001845713https://www.tvmaze.com/shows/45713/dolls-frontlineDolls' FrontlineAnimationChinese[Comedy, Anime, Science-Fiction]Ended5.05.02019-07-282020-12-16https://www.bilibili.com/bangumi/media/md2822989512:00[Wednesday]NaN20NaN51.0BilibiliNaNNoneNaNNaN373360.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/234/587413.jpghttps://static.tvmaze.com/uploads/images/original_untouched/234/587413.jpg<p>Re-imagines famous firearms as moe girls with machine bodies that are known as T-Dolls.</p>1613086641https://api.tvmaze.com/shows/45713https://api.tvmaze.com/episodes/2030020NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71973540https://www.tvmaze.com/episodes/1973540/please-wait-brother-1x19-episode-19Episode 19119.0regular2020-12-0212:002020-12-02T04:00:00+00:0037.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197354052038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81973541https://www.tvmaze.com/episodes/1973541/please-wait-brother-1x20-episode-20Episode 20120.0regular2020-12-0212:002020-12-02T04:00:00+00:0037.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197354152038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92066367https://www.tvmaze.com/episodes/2066367/chu-feng-yi-dian-shizi-1x04-episode-4Episode 414.0regular2020-12-022020-12-02T04:00:00+00:0030.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/206636754637https://www.tvmaze.com/shows/54637/chu-feng-yi-dian-shiziChu Feng: Yi Dian ShiziAnimationChinese[Action]Ended30.030.02020-11-182021-01-27http://weibo.com/u/6516179447[Wednesday]NaN8NaN118.0YoukuNaNNoneNaNNaN395235.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/305/764244.jpghttps://static.tvmaze.com/uploads/images/original_untouched/305/764244.jpg<p>Ordinary high school student Haoxuan Sun was taken hostage in a seemingly robbery and rescued by a girl wearing winged battledress with bee bionics designs. Haoxuan Sun's peaceful life was stirred by the girl – human bioengineering weapon Vanguard Liuli. Discovered that he is the "Son of Eden" wanted by all the great powers, Haoxuan Sun and Liuli have been searching for the truth and fight against the so-called destiny. At the same time, people around Haoxuan Sun, senpai Ye Bai who he has a crash on, his best friend, and many others, were discovered to have a second identities.<br /><br />The new BEE anime is based on the original manga plot. In addition, BEE manga's author Baimao personally joined the production team. The new BEE will also include two subplots entirely new to the viewers.</p>1617983545https://api.tvmaze.com/shows/54637https://api.tvmaze.com/episodes/2066376NaNChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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idurlnameseasonnumbertypeairdateairtimeairstampruntimesummaryrating.averageimage.mediumimage.original_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show._links.nextepisode.href_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel_embedded.show.image_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
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771979362https://www.tvmaze.com/episodes/1979362/rooneys-last-roll-1x04-memoriesMemories14.0regular2020-12-0215:002020-12-02T20:00:00+00:009.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/197936251888https://www.tvmaze.com/shows/51888/rooneys-last-rollRooney's Last RollScriptedEnglish[Drama, Comedy, Romance]Ended8.08.02020-11-112020-12-02https://www.youtube.com/playlist?list=PLVewHiZp3_LOgHGEQGGMplwBIs9hU7smb15:00[Wednesday]NaN21NaN274.0BratNaNNoneNaNNaN391739.0tt13419326https://static.tvmaze.com/uploads/images/medium_portrait/294/737014.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737014.jpg<p>When an old film roll goes missing at the film lab, an unexpected connection with a stranger helps Rooney confront her heartbreak and learn to move on.</p>1612024402https://api.tvmaze.com/shows/51888https://api.tvmaze.com/episodes/1979362NaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
781958865https://www.tvmaze.com/episodes/1958865/wwe-nxt-14x49-main-event-raquel-gonzalez-vs-shotzi-blackheart-in-a-wargames-advantage-ladder-matchMain Event: Raquel Gonzalez vs. Shotzi Blackheart in a WarGames Advantage Ladder Match1449.0regular2020-12-0220:002020-12-03T01:00:00+00:00121.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/19588652266https://www.tvmaze.com/shows/2266/wwe-nxtWWE NXTSportsEnglish[]Running120.077.02010-02-23Nonehttp://www.wwe.com/inside/networkschedule20:00[Tuesday]7.292NaN15.0WWE NetworkNaNNoneNaN25100.0144541.0tt1601141https://static.tvmaze.com/uploads/images/medium_portrait/401/1002762.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002762.jpg<p>Each Wednesday at 8:00 p.m. ET, WWE Superstars and Divas of tomorrow face off on <b>WWE NXT</b><i>,</i> a one-hour weekly show that features the brightest and best of WWE's rising stars. WWE NXT showcases the Superstars and Divas from WWE's Performance Center as well as appearances from WWE Superstars and Legends in an intimate setting. WWE NXT broadcasts from the state-of-the-art Full Sail LIVE venue on the Full Sail University in campus in Orlando, Florida.</p>1661969159https://api.tvmaze.com/shows/2266https://api.tvmaze.com/episodes/2383154NaNUnited StatesUSAmerica/New_Yorkhttps://api.tvmaze.com/episodes/236710730.0USA NetworkUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaN
791976920https://www.tvmaze.com/episodes/1976920/ruth-ruby-virtual-sleepover-challenges-2020-12-02-holiday-jingle-wrap-challengeHoliday Jingle Wrap Challenge20208.0regular2020-12-0221:252020-12-03T02:25:00+00:005.0<p>Happy Holidays! BFFs Ruby Rose Turner (Coop &amp; Cami Ask the World), Ruth Righi (Sydney to the Max), and special guest Issac Ryan Brown (Raven's Home) compete to see who can wrap the most gifts using oven mits and then unwrap them without making any noise!</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/382/956554.jpghttps://static.tvmaze.com/uploads/images/original_untouched/382/956554.jpghttps://api.tvmaze.com/episodes/197692045434https://www.tvmaze.com/shows/45434/ruth-ruby-virtual-sleepover-challengesRuth & Ruby Virtual Sleepover ChallengesTalk ShowEnglish[Comedy, Children, DIY]Running12.06.02019-08-09Nonehttps://disneynow.com/shows/ruth-and-ruby-virtual-sleepover-challenges21:25[Wednesday]NaN22NaN83.0DisneyNOWNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/285/714446.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/714446.jpg<p>Grab your sleeping bag and join BFFs Ruby Rose Turner (Coop &amp; Cami Ask the World) and Ruth Righi (Sydney to the Max) for the ultimate sleepover!</p>1639237512https://api.tvmaze.com/shows/45434https://api.tvmaze.com/episodes/1976924NaNUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
801945144https://www.tvmaze.com/episodes/1945144/noblesse-1x09-blood-contract-devoteBlood Contract / Devote19.0regular2020-12-0200:002020-12-03T05:00:00+00:0025.0<p>Raizel and Frankenstein first met in Lukedonia, the country of nobles. Raizel took Frankenstein, who was a noble hunter at the time, into his mansion to work as his butler. Frankenstein protected him for several years, but then some among the nobility who had unfavorable opinions of the duo began to revolt. What decision did Frankenstein and Raizel reach in response to this conflict?</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/718142.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/718142.jpghttps://api.tvmaze.com/episodes/194514449732https://www.tvmaze.com/shows/49732/noblesseNoblesseAnimationJapanese[Anime, Supernatural]Ended25.025.02015-12-042020-12-30https://noblesse-anime.com/00:00[Wednesday]NaN44NaN20.0CrunchyrollNaNNoneNaNNaN386818.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/268/670751.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670751.jpg<p>Raizel awakens from his 820-year slumber. He holds the special title of Noblesse, a pure-blooded Noble and protector of all other Nobles. In an attempt to protect Raizel, his servant Frankenstein enrolls him at Ye Ran High School, where Raizel learns the simple and quotidian routines of the human world through his classmates. However, the Union, a secret society plotting to take over the world, dispatches modified humans and gradually encroaches on Raizel's life, causing him to wield his mighty power to protect those around him... After 820 years of intrigue, the secrets behind his slumber are finally revealed, and Raizel's absolute protection as the Noblesse begins!</p>1648716882https://api.tvmaze.com/shows/49732https://api.tvmaze.com/episodes/1985214NaNNaNNaNNaNNaN132.0Tokyo MXJapanJPAsia/TokyoNaNNaNNaNNaNNaNNaN